https://scholars.lib.ntu.edu.tw/handle/123456789/626426
標題: | Liposome-based artificial cells: From gene expression to reconstitution of cellular functions and phenotypes | 作者: | Herianto, Samuel Chien, Po-Jen JA-AN ANNIE HO Tu, Hsiung-Lin |
關鍵字: | Artificial cells; Cell-free protein synthesis; Cellular reconstitution; Liposomes; Molecular functions | 公開日期: | 十一月-2022 | 出版社: | ELSEVIER | 卷: | 142 | 起(迄)頁: | 213156 | 來源出版物: | Biomaterials advances | 摘要: | Bottom-up approaches in creating artificial cells that can mimic natural cells have significant implications for both basic research and translational application. Among various artificial cell models, liposome is one of the most sophisticated systems. By encapsulating proteins and associated biomolecules, they can functionally reconstitute foundational features of biological cells, such as the ability to divide, communicate, and undergo shape deformation. Yet constructing liposome artificial cells from the genetic level, which is central to generate self-sustained systems remains highly challenging. Indeed, many studies have successfully established the expression of gene-coded proteins inside liposomes. Further, recent endeavors to build a direct integration of gene-expressed proteins for reconstituting molecular functions and phenotypes in liposomes have also significantly increased. Thus, this review presents the development of liposome-based artificial cells to demonstrate the process of gene-expressed proteins and their reconstitution to perform desired molecular and cell-like functions. The molecular and cellular phenotypes discussed here include the self-production of membrane phospholipids, division, shape deformation, self-DNA/RNA replication, fusion, and intercellular communication. Together, this review gives a comprehensive overview of gene-expressing liposomes that can stimulate further research of this technology and achieve artificial cells with superior properties in the future. |
URI: | https://scholars.lib.ntu.edu.tw/handle/123456789/626426 | ISSN: | 27729508 | DOI: | 10.1016/j.bioadv.2022.213156 |
顯示於: | 生化科技學系 |
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