Kin-ematic Exclusion in Active Matter: Modelling Mutual Inhibition in \textit{Pseudomonas aeruginosa} Sibling Colonies

TL;DR

This study reveals that sibling inhibition in Pseudomonas aeruginosa colonies results from nutrient depletion and motility inhibition, not from gel compression or quorum sensing, with a calibrated biophysical model explaining the phenomenon.

Contribution

The paper introduces a minimal biophysical model demonstrating nutrient-driven sibling inhibition in bacterial colonies, independent of quorum sensing or lethal effects.

Findings

Sibling inhibition is driven by nutrient depletion and motility inhibition.

The model accurately predicts inhibition strength based on initial nutrient levels.

Inhibition does not depend on gel compression or quorum sensing.

Abstract

The striking variety of macroscopic morphologies displayed by bacterial colonies depends on microscopic environmental and behavioural details in a manner that is currently not well understood. A surprising example is sibling inhibition, whereby isogenic bacterial colonies spreading in soft agar hydrogels tend to avoid each other and form sharp demarcation lines when growing nearby. Here we investigate this effect with the common pathogen \textit{Pseudomonas aeruginosa}, by combining quantitative density measurements with a minimal biophysical model. Our results show that the phenomenon does not depend on gel compression, lethal inhibition or quorum sensing-dependent cell communication. Instead, colony separation is driven by localised nutrient depletion through a dynamic feedback between growth and motility. The model, which is calibrated using experimental data, captures key observations including the dependence of inhibition strength on the initial nutrient concentration. This work establishes nutrient availability and non-lethal motility inhibition as central factors underlying sibling inhibition, providing a generalisable framework for microbial spatial dynamics with implications for understanding bacterial interactions in tissues, soils and engineered microbiomes.