Abstract
Antibiotic treatment is widely used for gastrointestinal diseases, often leading to drug resistance. However, the underlying mechanisms of drug resistance remain unclear. Mathematical modeling provides a powerful tool to explore the dynamics of antibiotic resistance, yet few models have considered the effect of biological noise, which originates from microscopic interactions between bacteria. In this study, we constructed a stochastic model based on the chemical master equations to investigate how stochastic noise influences the development of antibiotic resistance. Our simulations demonstrated that antibiotic resistance developed stepwise: while effective antibiotic treatments maintained the host's total pathogen numbers at healthy levels, the compositional balance shifted significantly through progressive increases in resistant pathogen proportions. Stochastic noise further amplified this shift and accelerated resistance by exacerbating post-treatment changes in the sensitive-to-resistant pathogen ratio. Finally, we found that the presence of coupling between different microbial communities can delay the onset of resistance and might even prevent its development. These results highlight noise's critical role in resistance development and suggest enhancing microbial interactions as a potential mitigation strategy.