利用小鼠种群的自然变异来了解宿主-肠道微生物组的相互作用

Q3 Pharmacology, Toxicology and Pharmaceutics Drug Discovery Today: Disease Models Pub Date : 2018-06-01 DOI:10.1016/j.ddmod.2019.08.003
Elin Org , Aldons J. Lusis
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引用次数: 4

摘要

理解肠道微生物群-宿主相互作用的一种方法,在这篇综述中描述,是研究自然变化的模式生物,其中环境因素可以控制,如何影响微生物组,反过来,微生物组如何与生理或临床特征相关联。该方法的一种变体,称为“系统遗传学”,是使用各种高通量技术(如微生物组学或微生物组和宿主的基因表达)来表征微生物组和宿主。通过将微生物组和宿主功能的变化与这种“分子表型”联系起来,可以产生假设,然后通过实验进行验证。为了以这种方式模拟人类肠道微生物群与宿主的相互作用,考虑到广泛的遗传资源和可用的实验工具,小鼠特别有用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Using the natural variation of mouse populations to understand host-gut microbiome interactions

One approach to understanding gut microbiome–host interactions, described in this review, is to examine how natural variation in a model organism, where environmental factors can be controlled, affects the microbiome and, in turn, how the microbiome is associated with physiological or clinical traits. A variation of this approach, termed “systems genetics” is to characterize both the microbiome and the host using various high throughput technologies, such as metabolomics or gene expression of the microbiome and the host. By relating variation in the microbiome and host functions to such “molecular phenotypes”, hypotheses can be generated and then experimentally tested. To model human gut microbiome–host interactions in this way, the mouse is particularly useful given the extensive body of genetic resources and experimental tools that are available.

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来源期刊
Drug Discovery Today: Disease Models
Drug Discovery Today: Disease Models Pharmacology, Toxicology and Pharmaceutics-Drug Discovery
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期刊介绍: Drug Discovery Today: Disease Models discusses the non-human experimental models through which inference is drawn regarding the molecular aetiology and pathogenesis of human disease. It provides critical analysis and evaluation of which models can genuinely inform the research community about the direct process of human disease, those which may have value in basic toxicology, and those which are simply designed for effective expression and raw characterisation.
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