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工程化微生物组以改善动植物健康。

Engineering Microbiomes to Improve Plant and Animal Health.

机构信息

Department of Integrative Biology, University of Texas at Austin, Austin, TX 78712, USA; Institute for Cellular and Molecular Biology, University of Texas at Austin, Austin, TX 78712, USA.

Department of Biology, University of California, 3401 Watkins Dr., Riverside, CA 92521, USA; Institute for Integrative Genome Biology, University of California, Riverside, CA 92521, USA.

出版信息

Trends Microbiol. 2015 Oct;23(10):606-617. doi: 10.1016/j.tim.2015.07.009. Epub 2015 Sep 25.

Abstract

Animal and plant microbiomes encompass diverse microbial communities that colonize every accessible host tissue. These microbiomes enhance host functions, contributing to host health and fitness. A novel approach to improve animal and plant fitness is to artificially select upon microbiomes, thus engineering evolved microbiomes with specific effects on host fitness. We call this engineering approach host-mediated microbiome selection, because this method selects upon microbial communities indirectly through the host and leverages host traits that evolved to influence microbiomes. In essence, host phenotypes are used as probes to gauge and manipulate those microbiome functions that impact host fitness. To facilitate research on host-mediated microbiome engineering, we explain and compare the principal methods to impose artificial selection on microbiomes; discuss advantages and potential challenges of each method; offer a skeptical appraisal of each method in light of these potential challenges; and outline experimental strategies to optimize microbiome engineering. Finally, we develop a predictive framework for microbiome engineering that organizes research around principles of artificial selection, quantitative genetics, and microbial community-ecology.

摘要

动植物微生物组包含了定植于宿主各个可及组织的多样化微生物群落。这些微生物组增强了宿主功能,促进了宿主健康和适应性。一种提高动植物适应性的新方法是对微生物组进行人为选择,从而通过特定的宿主效应来设计进化的微生物组,以影响宿主适应性。我们将这种工程方法称为宿主介导的微生物组选择,因为该方法通过宿主间接选择微生物群落,并利用宿主进化而来的特性来影响微生物组。从本质上讲,宿主表型被用作探测和操纵那些影响宿主适应性的微生物组功能的工具。为了促进宿主介导的微生物组工程研究,我们解释和比较了对微生物组施加人工选择的主要方法;讨论了每种方法的优缺点和潜在挑战;根据这些潜在挑战对每种方法进行了批判性评估;并概述了优化微生物组工程的实验策略。最后,我们开发了一个微生物组工程的预测框架,该框架围绕人工选择、数量遗传学和微生物群落生态学的原理组织研究。

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