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病毒-宿主相互作用的实验分析

Experimental Analysis of Viral-Host Interactions.

作者信息

Gillen Joseph, Nita-Lazar Aleksandra

机构信息

Laboratory of Immune System Biology, National Institute of Allergy and Infectious Diseases, National Institutes of Health, Bethesda, MD, United States.

出版信息

Front Physiol. 2019 Apr 11;10:425. doi: 10.3389/fphys.2019.00425. eCollection 2019.

Abstract

Viral and pathogen protein complexity is often limited by their relatively small genomes, thus critical functions are often accomplished by complexes of host and pathogen proteins. This requirement makes the study of host-pathogen interactions critical for the understanding of pathogenicity and virology. This review article discusses proteomic methods that offer an opportunity to experimentally identify and analyze the binding partners of a target protein and presents the representative studies performed with these methods. These methods divide into two classes: and . assays depend on bindings that occur outside of the normal cellular environment and include yeast two hybrids, pull-downs, and nucleic acid-programmable protein arrays (NAPPA). assays depend on bindings that occur inside of host cells and include affinity purification (AP) and proximity dependent labeling (PDL). Either or methods can be reliably used for generating protein-protein interactions networks but it is important to understand and recognize the limitations of the chosen methods when developing an interactomic network. In summary, proteomic methods can be extremely useful for interactomics but it is important to recognize the nature of the method when designing and analyzing an experiment.

摘要

病毒和病原体蛋白质的复杂性通常受到其相对较小基因组的限制,因此关键功能往往由宿主和病原体蛋白质的复合物来完成。这一需求使得宿主-病原体相互作用的研究对于理解致病性和病毒学至关重要。这篇综述文章讨论了蛋白质组学方法,这些方法为通过实验鉴定和分析目标蛋白质的结合伙伴提供了机会,并展示了用这些方法进行的代表性研究。这些方法分为两类: 和 。 分析依赖于在正常细胞环境之外发生的结合,包括酵母双杂交、下拉实验和核酸可编程蛋白质阵列(NAPPA)。 分析依赖于在宿主细胞内发生的结合,包括亲和纯化(AP)和邻近依赖性标记(PDL)。 或 方法都可以可靠地用于生成蛋白质-蛋白质相互作用网络,但在构建相互作用组网络时,了解并认识所选方法的局限性很重要。总之,蛋白质组学方法对于相互作用组学可能极其有用,但在设计和分析实验时认识方法的本质很重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/9ad6/6470254/96ac1526a2a8/fphys-10-00425-g001.jpg

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本文引用的文献

1
A guide to simple, direct, and quantitative binding assays.
J Biol Methods. 2017 Jan 20;4(1):e62. doi: 10.14440/jbm.2017.161. eCollection 2017.
2
An Integrative Approach to Virus-Host Protein-Protein Interactions.
Methods Mol Biol. 2018;1819:175-196. doi: 10.1007/978-1-4939-8618-7_8.
3
Viruses.STRING: A Virus-Host Protein-Protein Interaction Database.
Viruses. 2018 Sep 23;10(10):519. doi: 10.3390/v10100519.
4
Efficient proximity labeling in living cells and organisms with TurboID.
Nat Biotechnol. 2018 Oct;36(9):880-887. doi: 10.1038/nbt.4201. Epub 2018 Aug 20.
5
Global Interactomics Uncovers Extensive Organellar Targeting by Zika Virus.
Mol Cell Proteomics. 2018 Nov;17(11):2242-2255. doi: 10.1074/mcp.TIR118.000800. Epub 2018 Jul 23.
7
BioID: A Screen for Protein-Protein Interactions.
Curr Protoc Protein Sci. 2018 Feb 21;91:19.23.1-19.23.15. doi: 10.1002/cpps.51.
8
The interactome of EBV LMP1 evaluated by proximity-based BioID approach.
Virology. 2018 Mar;516:55-70. doi: 10.1016/j.virol.2017.12.033. Epub 2018 Jan 9.
9
Biotinylation by antibody recognition-a method for proximity labeling.
Nat Methods. 2018 Feb;15(2):127-133. doi: 10.1038/nmeth.4533. Epub 2017 Dec 18.
10
Proximity labeling: spatially resolved proteomic mapping for neurobiology.
Curr Opin Neurobiol. 2018 Jun;50:17-23. doi: 10.1016/j.conb.2017.10.015. Epub 2017 Nov 8.

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