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Synthetic biohybrid peptidoglycan oligomers enable pan-bacteria-specific labeling and imaging: in vitro and in vivo

Peptidoglycan is the core component of the bacterial cell wall, which makes it an attractive target for the development of bacterial targeting agents. Intercepting its enzymatic assembly with synthetic substrates allows for labeling and engineering of live bacterial cells. Over the past two decades,...

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Detalles Bibliográficos
Autores principales: He, Jing-Xi, Le Mai Hoang, Kim, Kho, Shu Hui, Guo, Zhong, Zhong, Wenbin, Venkata Thappeta, Kishore Reddy, Zamudio-Vázquez, Rubí, Hoo, Sin Ni, Xiong, Qirong, Duan, Hongwei, Yang, Liang, Chan-Park, Mary B., Liu, Xue-Wei
Formato: Online Artículo Texto
Lenguaje:English
Publicado: The Royal Society of Chemistry 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157403/
https://www.ncbi.nlm.nih.gov/pubmed/34122822
http://dx.doi.org/10.1039/c9sc06345e
Descripción
Sumario:Peptidoglycan is the core component of the bacterial cell wall, which makes it an attractive target for the development of bacterial targeting agents. Intercepting its enzymatic assembly with synthetic substrates allows for labeling and engineering of live bacterial cells. Over the past two decades, small-molecule-based labeling agents, such as antibiotics, d-amino acids or monosaccharides have been developed for probing biological processes in bacteria. Herein, peptidoglycan oligomers, substrates for transglycosylation, are prepared for the first time using a top-down approach, which starts from chitosan as a cheap feedstock. A high efficiency of labeling has been observed in all bacterial strains tested using micromolar substrates. In contrast, uptake into mammalian cells was barely observable. Additional mechanistic studies support a hypothesis of bacteria-specific metabolic labeling rather than non-specific binding to the bacterial surface. Eventually, its practicality in bacterial targeting capability is demonstrated in resistant strain detection and in vivo infection models.