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Investigating a holobiont: Microbiota perturbations and transkingdom networks

机译:研究全生命周期:微生物群扰动和变态网络

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摘要

The scientific community has recently come to appreciate that, rather than existing as independent organisms, multicellular hosts and their microbiota comprise a complex evolving superorganism or metaorganism, termed a holobiont. This point of view leads to a re-evaluation of our understanding of different physiological processes and diseases. In this paper we focus on experimental and computational approaches which, when combined in one study, allowed us to dissect mechanisms (traditionally named host-microbiota interactions) regulating holobiont physiology. Specifically, we discuss several approaches for microbiota perturbation, such as use of antibiotics and germ-free animals, including advantages and potential caveats of their usage. We briefly review computational approaches to characterize the microbiota and, more importantly, methods to infer specific components of microbiota (such as microbes or their genes) affecting host functions. One such approach called transkingdom network analysis has been recently developed and applied in our study. Finally, we also discuss common methods used to validate the computational predictions of host-microbiota interactions using in vitro and in vivo experimental systems.
机译:最近,科学界开始意识到,多细胞宿主及其微生物群不是由独立的有机体存在,而是由复杂的进化中的超有机体或超有机体组成,被称为全生命周期生物。这种观点导致对我们对不同生理过程和疾病的理解的重新评估。在本文中,我们着重于实验和计算方法,将它们结合在一起进行一项研究时,我们就可以剖析调节整体生物生理的机制(传统上称为宿主-菌群相互作用)。具体来说,我们讨论了几种解决微生物群扰动的方法,例如使用抗生素和无菌动物,包括其使用的优点和潜在的注意事项。我们简要回顾了表征微生物群的计算方法,更重要的是,推断影响宿主功能的微生物群特定成分(例如微生物或其基因)的方法。最近开发了一种这样的方法,称为“变态网络分析”。 最后,我们还讨论了使用体外和体内实验系统验证宿主-微生物相互作用的计算预测的常用方法。 。

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