Levy Roie, Borenstein Elhanan
Department of Genome Sciences; University of Washington; Seattle WA USA.
Department of Genome Sciences; University of Washington; Seattle WA USA; Department of Computer Science and Engineering; University of Washington; Seattle, WA USA; Santa Fe Institute; Santa Fe, NM USA.
Gut Microbes. 2014 Mar-Apr;5(2):265-70. doi: 10.4161/gmic.28261. Epub 2014 Feb 20.
The human microbiome is a key contributor to health and development. Yet little is known about the ecological forces that are at play in defining the composition of such host-associated communities. Metagenomics-based studies have uncovered clear patterns of community structure but are often incapable of distinguishing alternative structuring paradigms. In a recent study, we integrated metagenomic analysis with a systems biology approach, using a reverse ecology framework to model numerous human microbiota species and to infer metabolic interactions between species. Comparing predicted interactions with species composition data revealed that the assembly of the human microbiome is dominated at the community level by habitat filtering. Furthermore, we demonstrated that this habitat filtering cannot be accounted for by known host phenotypes or by the metabolic versatility of the various species. Here we provide a summary of our findings and offer a brief perspective on related studies and on future approaches utilizing this metagenomic systems biology framework.
人类微生物组是健康与发育的关键贡献者。然而,对于在定义此类宿主相关群落组成中起作用的生态力量,我们知之甚少。基于宏基因组学的研究已经揭示了群落结构的清晰模式,但往往无法区分不同的构建范式。在最近的一项研究中,我们将宏基因组分析与系统生物学方法相结合,使用逆向生态学框架对众多人类微生物物种进行建模,并推断物种间的代谢相互作用。将预测的相互作用与物种组成数据进行比较后发现,人类微生物组的组装在群落水平上主要受栖息地过滤的支配。此外,我们证明这种栖息地过滤不能用已知的宿主表型或各种物种的代谢多功能性来解释。在此,我们总结我们的发现,并简要展望相关研究以及利用这种宏基因组系统生物学框架的未来方法。