The effect of stochastic noise on antibiotic resistance in intestinal flora.

IF 3.5 2区 生物学 Q1 MATHEMATICAL & COMPUTATIONAL BIOLOGY
Aofei Hu, Ling Yang, Jie Yan
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引用次数: 0

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.

随机噪声对肠道菌群抗生素耐药性的影响。
抗生素治疗广泛用于胃肠道疾病,经常导致耐药性。然而,耐药性的潜在机制仍不清楚。数学建模为探索抗生素耐药性的动态提供了一个强大的工具,但很少有模型考虑到生物噪声的影响,它起源于细菌之间的微观相互作用。在本研究中,我们建立了一个基于化学主方程的随机模型来研究随机噪声如何影响抗生素耐药性的发展。我们的模拟表明,抗生素耐药性是逐步发展的:虽然有效的抗生素治疗使宿主的总病原体数量保持在健康水平,但随着耐药病原体比例的逐渐增加,组成平衡发生了显著变化。随机噪声进一步放大了这种转变,并通过加剧治疗后敏感-耐药病原体比率的变化加速了耐药性。最后,我们发现不同微生物群落之间的偶联可以延缓耐药性的发生,甚至可能阻止其发展。这些结果强调了噪声在耐药性发展中的关键作用,并建议加强微生物相互作用作为潜在的缓解策略。
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来源期刊
NPJ Systems Biology and Applications
NPJ Systems Biology and Applications Mathematics-Applied Mathematics
CiteScore
5.80
自引率
0.00%
发文量
46
审稿时长
8 weeks
期刊介绍: npj Systems Biology and Applications is an online Open Access journal dedicated to publishing the premier research that takes a systems-oriented approach. The journal aims to provide a forum for the presentation of articles that help define this nascent field, as well as those that apply the advances to wider fields. We encourage studies that integrate, or aid the integration of, data, analyses and insight from molecules to organisms and broader systems. Important areas of interest include not only fundamental biological systems and drug discovery, but also applications to health, medical practice and implementation, big data, biotechnology, food science, human behaviour, broader biological systems and industrial applications of systems biology. We encourage all approaches, including network biology, application of control theory to biological systems, computational modelling and analysis, comprehensive and/or high-content measurements, theoretical, analytical and computational studies of system-level properties of biological systems and computational/software/data platforms enabling such studies.
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