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代谢组学揭示了微生物结构、相互作用以及在定义的群落中对环境干扰的响应的动态调节的见解。

Metaproteomics reveals insights into microbial structure, interactions, and dynamic regulation in defined communities as they respond to environmental disturbance.

机构信息

Biosciences Division, Oak Ridge National Laboratory, 37831, Oak Ridge, Tennessee, United States.

Department of Genome Science and Technology, University of Tennessee-Knoxville, 37996, Knoxville, Tennessee, United States.

出版信息

BMC Microbiol. 2021 Nov 8;21(1):308. doi: 10.1186/s12866-021-02370-4.


DOI:10.1186/s12866-021-02370-4
PMID:34749649
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8574000/
Abstract

BACKGROUND: Microbe-microbe interactions between members of the plant rhizosphere are important but remain poorly understood. A more comprehensive understanding of the molecular mechanisms used by microbes to cooperate, compete, and persist has been challenging because of the complexity of natural ecosystems and the limited control over environmental factors. One strategy to address this challenge relies on studying complexity in a progressive manner, by first building a detailed understanding of relatively simple subsets of the community and then achieving high predictive power through combining different building blocks (e.g., hosts, community members) for different environments. Herein, we coupled this reductionist approach with high-resolution mass spectrometry-based metaproteomics to study molecular mechanisms driving community assembly, adaptation, and functionality for a defined community of ten taxonomically diverse bacterial members of Populus deltoides rhizosphere co-cultured either in a complex or defined medium. RESULTS: Metaproteomics showed this defined community assembled into distinct microbiomes based on growth media that eventually exhibit composition and functional stability over time. The community grown in two different media showed variation in composition, yet both were dominated by only a few microbial strains. Proteome-wide interrogation provided detailed insights into the functional behavior of each dominant member as they adjust to changing community compositions and environments. The emergence and persistence of select microbes in these communities were driven by specialization in strategies including motility, antibiotic production, altered metabolism, and dormancy. Protein-level interrogation identified post-translational modifications that provided additional insights into regulatory mechanisms influencing microbial adaptation in the changing environments. CONCLUSIONS: This study provides high-resolution proteome-level insights into our understanding of microbe-microbe interactions and highlights specialized biological processes carried out by specific members of assembled microbiomes to compete and persist in changing environmental conditions. Emergent properties observed in these lower complexity communities can then be re-evaluated as more complex systems are studied and, when a particular property becomes less relevant, higher-order interactions can be identified.

摘要

背景:植物根际成员之间的微生物-微生物相互作用很重要,但仍知之甚少。由于自然生态系统的复杂性和对环境因素的有限控制,全面了解微生物用于合作、竞争和生存的分子机制一直具有挑战性。应对这一挑战的一种策略依赖于逐步研究复杂性,首先在相对简单的群落子集上建立详细的理解,然后通过为不同环境组合不同的构建块(例如宿主、群落成员)来实现高预测能力。在这里,我们将这种简化方法与基于高分辨率质谱的宏蛋白质组学相结合,研究了驱动群落组装、适应和功能的分子机制,用于共培养的十个具有分类多样性的细菌成员的定义群落Populus deltoides 根际,无论是在复杂还是定义的培养基中。

结果:宏蛋白质组学表明,该定义群落根据生长培养基组装成不同的微生物组,最终随着时间的推移表现出组成和功能的稳定性。在两种不同培养基中生长的群落表现出组成上的差异,但都仅由少数几种微生物菌株主导。全蛋白质组分析深入了解了每个优势成员的功能行为,因为它们会根据群落组成和环境的变化进行调整。这些群落中选择微生物的出现和持续存在是由专门的策略驱动的,包括运动性、抗生素生产、代谢改变和休眠。蛋白质水平的询问提供了有关影响微生物在不断变化的环境中适应的调节机制的额外见解。

结论:本研究提供了对微生物-微生物相互作用的高分辨率蛋白质组学理解,并强调了组装微生物组中特定成员执行的专门生物学过程,以在不断变化的环境条件下竞争和生存。在这些较低复杂性的群落中观察到的新兴特性可以在研究更复杂的系统时重新评估,并且当特定特性变得不那么相关时,可以确定更高阶的相互作用。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/bd275d02f3dc/12866_2021_2370_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/44033e094e0e/12866_2021_2370_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/98c49c695871/12866_2021_2370_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/19ab14f42545/12866_2021_2370_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/2bf9dca1797e/12866_2021_2370_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/6268bc591607/12866_2021_2370_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/bd275d02f3dc/12866_2021_2370_Fig6_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/44033e094e0e/12866_2021_2370_Fig1_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/98c49c695871/12866_2021_2370_Fig2_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/19ab14f42545/12866_2021_2370_Fig3_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/2bf9dca1797e/12866_2021_2370_Fig4_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/6268bc591607/12866_2021_2370_Fig5_HTML.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/dc46/8574000/bd275d02f3dc/12866_2021_2370_Fig6_HTML.jpg

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Biology (Basel). 2021-6-2

[2]
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Comput Struct Biotechnol J. 2021-4-9

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