Building protein networks in synthetic systems from the bottom-up

被引:11
|
作者
Shim, Jiyoung [1 ]
Zhou, Chuqing [1 ]
Gong, Ting [1 ]
Iserlis, Dasha Aleksandra [1 ]
Linjawi, Hamad Abdullah [1 ]
Wong, Matthew [1 ]
Pan, Tingrui [1 ,2 ]
Tan, Cheemeng [1 ]
机构
[1] Univ Calif Davis, Dept Biomed Engn, Davis, CA 95616 USA
[2] Univ Sci & Technol, Suzhou Inst Adv Res, Suzhou, Peoples R China
关键词
Protein network; In vitro; Genetic circuit; Automation; High throughput; Bottom-up; Protein purification; Encapsulation; Artificial cell; Cell-free; ESCHERICHIA-COLI; MEMBRANE; PURIFICATION; RECONSTITUTION; EXPRESSION; MOLECULES; PEPTIDES; FUSION; CELLS; STEP;
D O I
10.1016/j.biotechadv.2021.107753
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
The recent development of synthetic biology has expanded the capability to design and construct protein networks outside of living cells from the bottom-up. The new capability has enabled us to assemble protein networks for the basic study of cellular pathways, expression of proteins outside cells, and building tissue materials. Furthermore, the integration of natural and synthetic protein networks has enabled new functions of synthetic or artificial cells. Here, we review the underlying technologies for assembling protein networks in liposomes, waterin-oil droplets, and biomaterials from the bottom-up. We cover the recent applications of protein networks in biological transduction pathways, energy self-supplying systems, cellular environmental sensors, and cell-free protein scaffolds. We also review new technologies for assembling protein networks, including multiprotein purification methods, high-throughput assay screen platforms, and controllable fusion of liposomes. Finally, we present existing challenges towards building protein networks that rival the complexity and dynamic response akin to natural systems. This review addresses the gap in our understanding of synthetic and natural protein networks. It presents a vision towards developing smart and resilient protein networks for various biomedical applications.
引用
收藏
页数:15
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