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Agent Based Modeling of Human Gut Microbiome Interactions and Perturbations

机译:基于代理的人类肠道微生物组相互作用和扰动建模

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Background Intestinal microbiota plays an important role in the human health. It is involved in the digestion and protects the host against external pathogens. Examination of the intestinal microbiome interactions is required for understanding of the community influence on host health. Studies of the microbiome can provide insight on methods of improving health, including specific clinical procedures for individual microbial community composition modification and microbiota correction by colonizing with new bacterial species or dietary changes. Methodology/Principal Findings In this work we report an agent-based model of interactions between two bacterial species and between species and the gut. The model is based on reactions describing bacterial fermentation of polysaccharides to acetate and propionate and fermentation of acetate to butyrate. Antibiotic treatment was chosen as disturbance factor and used to investigate stability of the system. System recovery after antibiotic treatment was analyzed as dependence on quantity of feedback interactions inside the community, therapy duration and amount of antibiotics. Bacterial species are known to mutate and acquire resistance to the antibiotics. The ability to mutate was considered to be a stochastic process, under this suggestion ratio of sensitive to resistant bacteria was calculated during antibiotic therapy and recovery. Conclusion/Significance The model confirms a hypothesis of feedbacks mechanisms necessity for providing functionality and stability of the system after disturbance. High fraction of bacterial community was shown to mutate during antibiotic treatment, though sensitive strains could become dominating after recovery. The recovery of sensitive strains is explained by fitness cost of the resistance. The model demonstrates not only quantitative dynamics of bacterial species, but also gives an ability to observe the emergent spatial structure and its alteration, depending on various feedback mechanisms. Visual version of the model shows that spatial structure is a key factor, which helps bacteria to survive and to adapt to changed environmental conditions.
机译:背景技术肠道菌群在人类健康中起着重要作用。它参与消化并保护宿主免受外部病原体侵害。为了了解社区对宿主健康的影响,需要检查肠道微生物组的相互作用。微生物组的研究可以提供有关改善健康状况的方法的见解,包括通过移入新细菌种类或改变饮食来改变个体微生物群落组成和纠正微生物群的特定临床程序。方法/主要发现在这项工作中,我们报告了两种细菌之间以及物种与肠道之间相互作用的基于主体的模型。该模型基于描述多糖细菌发酵为乙酸盐和丙酸盐以及乙酸盐发酵为丁酸盐的反应。选择抗生素治疗作为干扰因素,并用于研究系统的稳定性。分析抗生素治疗后的系统恢复情况,取决于社区内部反馈相互作用的数量,治疗时间和抗生素的数量。已知细菌种类会突变并获得对抗生素的抗性。突变的能力被认为是随机过程,在这种建议下,在抗生素治疗和恢复期间计算了对耐药细菌敏感的比例。结论/重要性该模型证实了一种反馈机制的假设,该反馈机制对于在扰动后提供系统功能和稳定性是必要的。尽管在恢复后敏感菌株可能占主导地位,但在抗生素治疗期间细菌群落的高部分已显示出突变。敏感菌株的恢复通过抗性的适应性成本来解释。该模型不仅演示了细菌物种的定量动力学,而且还提供了根据各种反馈机制观察出现的空间结构及其变化的能力。该模型的可视化版本显示空间结构是关键因素,可帮助细菌生存并适应变化的环境条件。

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