Suppr超能文献

利用合成生物学方法改造外膜囊泡的机会。

Opportunities for engineering outer membrane vesicles using synthetic biology approaches.

作者信息

Kelwick Richard J R, Webb Alexander J, Freemont Paul S

机构信息

Section of Structural and Synthetic Biology, Department of Infectious Disease, Imperial College London, London SW7 2AZ, UK.

Authors contributed equally.

出版信息

Extracell Vesicles Circ Nucl Acids. 2023 Jun 8;4(2):255-261. doi: 10.20517/evcna.2023.21. eCollection 2023.

Abstract

Gram-negative bacteria naturally shed lipid vesicles, which contain complex molecular cargoes, from their outer membrane. These outer membrane vesicles (OMVs) have important biological functions relating to microbial stress responses, microbiome regulation, and host-pathogen interactions. OMVs are also attractive vehicles for delivering drugs, vaccines, and other therapeutic agents because of their ability to interact with host cells and their natural immunogenic properties. OMVs are also set to have a positive impact on other biotechnological and medical applications including diagnostics, bioremediation, and metabolic engineering. We envision that the field of synthetic biology offers a compelling opportunity to further expand and accelerate the foundational research and downstream applications of OMVs in a range of applications including the provision of OMV-based healthcare technologies. In our opinion, we discuss how current and potential future synergies between OMV research and synthetic biology approaches might help to further accelerate OMV research and real-world applications for the benefit of animal and human health.

摘要

革兰氏阴性菌会自然地从其外膜脱落含有复杂分子货物的脂质囊泡。这些外膜囊泡(OMV)在微生物应激反应、微生物群调节和宿主-病原体相互作用方面具有重要的生物学功能。由于OMV能够与宿主细胞相互作用并具有天然的免疫原性,它们也是递送药物、疫苗和其他治疗剂的有吸引力的载体。OMV还将对包括诊断、生物修复和代谢工程在内的其他生物技术和医学应用产生积极影响。我们设想合成生物学领域提供了一个极具吸引力的机会,可以进一步扩展和加速OMV在一系列应用中的基础研究和下游应用,包括提供基于OMV的医疗技术。我们认为,我们将讨论OMV研究与合成生物学方法之间当前和潜在的未来协同作用如何有助于进一步加速OMV研究和实际应用,以造福动物和人类健康。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/268b/11648402/699c5589cd46/evcna-4-2-255.fig.1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验