# Linking spatial drug heterogeneity to microbial growth dynamics in theory and experiment

## TL;DR

This study shows that the spatial arrangement of antibiotics, not just the total amount, strongly affects bacterial population outcomes in structured environments.

## Contribution

The study introduces a robot-automated system and theoretical framework to analyze spatial drug heterogeneity's impact on microbial growth dynamics.

## Key findings

- Bacterial population persistence depends on drug spatial arrangement even with fixed total drug amount.
- Theoretical and experimental approaches identified drug arrangements that maximize growth or fastest decline.
- Results extend classical growth models to heterogeneous environments and suggest spatial dosing strategies matter.

## Abstract

Drugs play a central role in limiting bacterial population spread, yet laboratory studies typically assume well-mixed environments when assessing microbial drug responses. In contrast, bacteria in the human body often occupy spatially structured habitats where drug concentrations vary. Understanding how this heterogeneity shapes growth and decline is therefore essential for controlling infections and mitigating resistance evolution. Here, we developed a minimal robot-automated system to study how spatial drug heterogeneity affects short-term population dynamics in E. faecalis, a Gram-positive opportunistic pathogen. This system was combined with a theoretical framework to interpret and explain the observed outcomes. We first recapitulated the classic critical-patch-size model result: in a spatially homogeneous environment, a population persists in a finite domain only when growth outpaces diffusive losses at the boundaries. In heterogeneous environments, we found certain conditions that population persistence can depend critically on the spatial arrangement of the drug, even when its total amount is fixed. Using theoretical and experimental approaches, we identified the arrangements that produce the strongest growth and the fastest decline, revealing the range of possible outcomes under drug heterogeneity. We further tested this framework in more complex environments, including ring-shaped communities, and observed consistent arrangement-dependent behavior. Overall, our results extend the classical growth-condition framework to general heterogeneous environments and demonstrate that spatial drug arrangement - not only total dose - can strongly influence bacterial population dynamics. These findings highlight the importance of spatially structured dosing strategies and motivate further theoretical and experimental investigation.

Understanding how bacteria respond, grow and spread in the presence of antibiotics is crucial for fighting infections and preventing drug resistance. In many real-world environments, like the human body, antibiotics are not spread evenly. Instead, they often create a patchwork of high- and low-drug regions. In this study, we built a simple lab system that mimics this kind of uneven landscape, using a common bacterium existing in human’s gut and a robotic platform. We found that the overall outcome, whether the bacterial population grows or dies out, depends not just on how much drug is present, but on how and where exactly the drug is placed. Even with the same total drug amount, different spatial layouts led to very different results. Using computer simulations and mathematical tools, we showed that this effect could be predicted and explained. Our findings highlight the importance of drug distribution in treatment strategies and suggest that how antibiotics are arranged in space may be just as important as how much is used.