Programmable living assembly of materials by bacterial adhesion

The field of engineered living materials aims to construct functional materials with desirable properties of natural living systems. A recent study demonstrated the programmed self-assembly of bacterial populations by engineered adhesion. Here we use this strategy to engineer self-healing living mat...

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Published inNature chemical biology Vol. 18; no. 3; pp. 289 - 294
Main Authors Chen, Baizhu, Kang, Wei, Sun, Jing, Zhu, Runtao, Yu, Yue, Xia, Aiguo, Yu, Mei, Wang, Meng, Han, Jinyu, Chen, Yixuan, Teng, Lijun, Tian, Qiong, Yu, Yin, Li, Guanglin, You, Lingchong, Liu, Zhiyuan, Dai, Zhuojun
Format Journal Article
LanguageEnglish
Published New York Nature Publishing Group US 01.03.2022
Nature Publishing Group
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Summary:The field of engineered living materials aims to construct functional materials with desirable properties of natural living systems. A recent study demonstrated the programmed self-assembly of bacterial populations by engineered adhesion. Here we use this strategy to engineer self-healing living materials with versatile functions. Bacteria displaying outer membrane-anchored nanobody–antigen pairs are cultured separately and, when mixed, adhere to each other to enable processing into functional materials, which we term living assembled material by bacterial adhesion (LAMBA). LAMBA is programmable and can be functionalized with extracellular moieties up to 545 amino acids. Notably, the adhesion between nanobody–antigen pairs in LAMBA leads to fast recovery under stretching or bending. By exploiting this feature, we fabricated wearable LAMBA sensors that can detect bioelectrical or biomechanical signals. Our work establishes a scalable approach to produce genetically editable and self-healable living functional materials that can be applied in biomanufacturing, bioremediation and soft bioelectronics assembly. Bacterial populations, programmed to self-assemble by adhesion of nanobody–antigen pairs, can be processed into living materials (LAMBA) that are scalable, self-healing and programmable through functionalization with diverse proteins.
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ISSN:1552-4450
1552-4469
DOI:10.1038/s41589-021-00934-z