Towards predictive models of the human gut microbiome.

Towards predictive models of the human gut microbiome.
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迈向人类肠道微生物组的预测模型。

DOI:
10.1016/j.jmb.2014.03.017
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发表时间:
2014-11-25
影响因子:
5.6
通讯作者:
Xavier JB
Xavier JB
中科院分区:
生物学2区
文献类型:
--
作者:
Bucci V;Xavier JB

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肠道微生物群是一个易受外部扰动(如饮食变化和抗生素治疗)影响的生态系统。微生物群落的数学模型对合理设计适合微生物群的饮食和治疗具有重要价值。在这里,我们讨论了另一个领域的进展,废水处理生物反应器的微生物群落工程,如何激发肠道微生物群的机械数学模型的发展。我们回顾了目前生物反应器建模和肠道微生物群建模的最新进展。数学建模可以从宏基因组研究产生的大量数据中受益匪浅,但数据驱动的方法,如网络推理,旨在预测微生物组动力学,而没有明确的机制知识,似乎更适合建模这些数据。最后,我们讨论了微生物组霰弹枪测序和代谢建模方法(如通量平衡分析)的整合如何实现肠道微生物群机制模型的承诺。
The intestinal microbiota is an ecosystem susceptible to external perturbations such as dietary changes and antibiotic therapies. Mathematical models of microbial communities could be of great value in the rational design of microbiota-tailoring diets and therapies. Here, we discuss how advances in another field, engineering of microbial communities for wastewater treatment bioreactors, could inspire development of mechanistic mathematical models of the gut microbiota. We review the current state-of-the-art in bioreactor modeling and current efforts in modeling the intestinal microbiota. Mathematical modeling could benefit greatly from the deluge of data emerging from metagenomic studies, but data-driven approaches such as network inference that aim to predict microbiome dynamics without explicit mechanistic knowledge seem better suited to model these data. Finally, we discuss how the integration of microbiome shotgun sequencing and metabolic modeling approaches such as flux balance analysis may fulfill the promise of a mechanistic model of the intestinal microbiota.
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