DOAJ Open Access 2023

Colorimetric Detection and Killing of Bacteria by Enzyme-Instructed Self-Aggregation of Peptide-Modified Gold Nanoparticles

Dan Yin Xiao Li Xin Wang Jin-Zhou Liu Wen-Zhi She +4 lainnya

Abstrak

Bacterial infections seriously threaten human safety. Therefore, it is very important to develop a method for bacterial detection and treatment with rapid response, high sensitivity, and simple operation. A peptide CF<sub>4</sub>KY<sup>P</sup> (C, cysteine; F<sub>4</sub>, phenylalanine tetrapeptide; K, lysine; Y<sup>P</sup>, phosphorylated tyrosine) functionalized gold nanoparticle (AuNPs-CF<sub>4</sub>KY<sup>P</sup>) was synthesized for simultaneous detection and treatment of bacteria based on bacterial alkaline phosphatase (ALP). In solution, ALP can induce AuNPs-CF<sub>4</sub>KY<sup>P</sup> aggregation and produce significant color changes. After encountering bacteria, monodisperse AuNPs-CF<sub>4</sub>KY<sup>P</sup> can aggregate/assemble in situ on the surface of the bacterial membrane, change the color of the solution from wine red to grey, destroy the bacterial membrane structure, and induce the production of a large number of reactive oxygen species within the bacteria. The absorption change of AuNPs-CF<sub>4</sub>KY<sup>P</sup> solution has a good linear relationship with the number of bacteria. Furthermore, the aggregation of AuNPs-CF<sub>4</sub>KY<sup>P</sup> kills approximately 80% of <i>Salmonella typhimurium</i>. By combining enzyme-instructed peptide self-assembly technology and colorimetric analysis technology, we achieve rapid and sensitive colorimetric detection and killing of bacteria.

Topik & Kata Kunci

Penulis (9)

D

Dan Yin

X

Xiao Li

X

Xin Wang

J

Jin-Zhou Liu

W

Wen-Zhi She

J

Jiahui Liu

J

Jian Ling

R

Rong Sheng Li

Q

Qiue Cao

Format Sitasi

Yin, D., Li, X., Wang, X., Liu, J., She, W., Liu, J. et al. (2023). Colorimetric Detection and Killing of Bacteria by Enzyme-Instructed Self-Aggregation of Peptide-Modified Gold Nanoparticles. https://doi.org/10.3390/chemosensors11090484

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Informasi Jurnal
Tahun Terbit
2023
Sumber Database
DOAJ
DOI
10.3390/chemosensors11090484
Akses
Open Access ✓