PDF(Pubmed)
Abstract：
The explosion of microbiome analyses has helped identify individual microorganisms and microbial communities driving human health and disease, but how these communities function is still an open question. For example, the role for the incredibly complex metabolic interactions among microbial species cannot easily be resolved by current experimental approaches such as 16S rRNA gene sequencing, metagenomics and/or metabolomics. Resolving such metabolic interactions is particularly challenging in the context of polymicrobial communities where metabolite exchange has been reported to impact key bacterial traits such as virulence and antibiotic treatment efficacy. As novel approaches are needed to pinpoint microbial determinants responsible for impacting community function in the context of human health and to facilitate the development of novel anti-infective and antimicrobial drugs, here we review, from the viewpoint of experimentalists, the latest advances in metabolic modeling, a computational method capable of predicting metabolic capabilities and interactions from individual microorganisms to complex ecological systems. We use selected examples from the literature to illustrate how metabolic modeling has been utilized, in combination with experiments, to better understand microbial community function. Finally, we propose how such combined, cross-disciplinary efforts can be utilized to drive laboratory work and drug discovery moving forward.
摘要：
微生物组分析的爆炸式增长有助于识别驱动人类健康和疾病的个体微生物和微生物群落。但是这些社区如何运作仍然是一个悬而未决的问题。例如,微生物物种之间极其复杂的代谢相互作用的作用无法通过当前的实验方法（如16SrRNA基因测序）轻松解决，宏基因组学和/或代谢组学。解决这种代谢相互作用在多微生物群落的背景下尤其具有挑战性,其中据报道代谢物交换影响关键细菌性状,例如毒力和抗生素治疗功效。由于需要新的方法来查明在人类健康背景下影响社区功能的微生物决定因素，并促进新型抗感染和抗微生物药物的开发，在这里我们回顾一下，从实验主义者的角度来看，代谢建模的最新进展，一种能够预测个体微生物与复杂生态系统之间的代谢能力和相互作用的计算方法。我们使用文献中选定的例子来说明代谢建模是如何利用的，结合实验，更好地了解微生物群落的功能。最后,我们提出如何结合，可以利用跨学科的努力来推动实验室工作和药物发现向前发展。
