Heinken Almut, Thiele Ines
Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belval, Luxembourg.
Wiley Interdiscip Rev Syst Biol Med. 2015 Jul-Aug;7(4):195-219. doi: 10.1002/wsbm.1301. Epub 2015 Apr 30.
The human gut microbiota performs essential functions for host and well-being, but has also been linked to a variety of disease states, e.g., obesity and type 2 diabetes. The mammalian body fluid and tissue metabolomes are greatly influenced by the microbiota, with many health-relevant metabolites being considered 'mammalian-microbial co-metabolites'. To systematically investigate this complex host-microbial co-metabolism, a systems biology approach integrating high-throughput data and computational network models is required. Here, we review established top-down and bottom-up systems biology approaches that have successfully elucidated relationships between gut microbiota-derived metabolites and host health and disease. We focus particularly on the constraint-based modeling and analysis approach, which enables the prediction of mechanisms behind metabolic host-microbe interactions on the molecular level. We illustrate that constraint-based models are a useful tool for the contextualization of metabolomic measurements and can further our insight into host-microbe interactions, yielding, e.g., in potential novel drugs and biomarkers.
人类肠道微生物群对宿主的健康起着至关重要的作用,但也与多种疾病状态有关,如肥胖症和2型糖尿病。哺乳动物的体液和组织代谢组受到微生物群的极大影响,许多与健康相关的代谢物被认为是“哺乳动物-微生物共代谢物”。为了系统地研究这种复杂的宿主-微生物共代谢,需要一种整合高通量数据和计算网络模型的系统生物学方法。在这里,我们回顾了已建立的自上而下和自下而上的系统生物学方法,这些方法成功地阐明了肠道微生物群衍生的代谢物与宿主健康和疾病之间的关系。我们特别关注基于约束的建模和分析方法,该方法能够在分子水平上预测代谢宿主-微生物相互作用背后的机制。我们表明,基于约束的模型是代谢组学测量背景化的有用工具,可以加深我们对宿主-微生物相互作用的理解,例如产生潜在的新型药物和生物标志物。