代谢建模揭示了在多个人类干预试验中,益生菌和益生菌治疗疗效的决定因素
Nick Quinn-Bohmann1, Alex V Carr1, Sean M Gibbons1,2,3,4,5
1Institute for Systems Biology, Seattle, Washington, United States of America.
PLoS biology
|February 19, 2026
概括
预测益生菌和益生菌疗法的成功是具有挑战性的. 微生物社区规模代谢模型 (MCMMs) 准确预测益生菌移植和短链脂肪酸 (SCFA) 生产,指导个性化微生物群干预.
科学领域:
- 微生物组研究的研究.
- 代谢建模 代谢建模
- 个性化的营养 个性化的营养
背景情况:
- 益生菌和益生菌干预表明由于复杂的宿主-微生物群-饮食相互作用的可变结果.
- 预测个体对微生物组疗法的反应仍然是一个重大挑战.
- 微生物社区规模代谢模型 (MCMMs) 为预测干预成功提供了一个潜在的解决方案.
研究的目的:
- 为了利用MCMM来预测益生菌植入和短链脂肪酸 (SCFA) 生产.
- 用人类临床试验数据评估MCMM预测的准确性.
- 探索MCMMs在指导个性化微生物组介导干预方面的潜力.
主要方法:
- 使用微生物社区规模代谢模型 (MCMMs).
- 应用了MCMMs对来自两个人类临床试验队列的数据,其中包括益生菌和益生菌干预措施.
- 与测量的益生菌植入和SCFA生产相比,验证的MCMM预测.
主要成果:
- 在预测不同种群中的益生菌植入方面,MCMMs获得了75% - 80%的准确性.
- MCMMs准确地捕捉了预测的SCFA生产中的处理驱动的转变.
- 模型预测的Akkermansia muciniphila的生长与改善的葡萄糖代谢有关.
- MCMMs揭示了饮食纤维预测反应的显著个体间变异性,与心脏代谢健康变化有关.
结论:
- 多种微生物菌体显示出预测个体对微生物干预措施的反应的强大潜力.
- 代谢建模可以提供对治疗疗效机制的见解.
- 由MCMMs指导的个性化益生菌选择可能会提高益生菌的疗效.
- MCMMs可以指导个性化微生物组介导干预,以改善健康结果.
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