Adenosine Triphosphate-Responsive Glyconanorods through Self-Assembly of β-Cyclodextrin-Based Glycoconjugates for Targeted and Effective Bacterial Sensing and Killing.
Feihu BiJin ZhangRui XieDeshui YuHanchen WeiYulong WangZan HuaXiangming QiBo HuangGuang YangPublished in: Biomacromolecules (2023)
Polymer-based nanomaterials have exhibited promising alternative avenues to combat the globe challenge of multidrug-resistant bacterial infection. However, most of the reported polymeric nanomaterials have facially linear amphiphilic structures with positive net charges, which may lead to nonspecific binding, high hemolysis, and uncontrollable self-organization, limiting their practical applications. In this contribution, we report a one-dimensional glyconanorod (GNR) through self-assembly of well-defined β-cyclodextrin-based glycoconjugates (RMan) featuring hydrophobic carbon-based chains and amide rhodamines with an adenosine triphosphate (ATP)-recognition site and targeted and hydrophilic mannoses and positively net-charged ethylene amine groups. The GNRs show superior targeting sensing and killing for Gram-negative Escherichia coli ( E. coli ) dominantly through the multivalent recognition between mannoses on the nanorod and the lectin on the surface of E. coli . Moreover, red fluorescence was light on due to the hydrogen bonding between amide rhodamine and ATP. Benefiting from the designs, the GNRs are capable of possessing a higher therapeutic index and of encapsulating other antibiotics. They exhibit an enhanced effect against E. coli strains. Intriguingly, the GNRs displayed a more reduced hemolysis effect and lower cytotoxicity compared to that of ethylene glyco-modified nanorods. These results reveal that the glyconanomaterials not only feature superior and targeted bacterial sensing and antibacterial activity, but also better biocompatibility compared with the widely used PEG-covered nanomaterials. Furthermore, the in vivo studies demonstrate that the targeted and ATP-responsive GNRs complexed with antibiotics showed better treatment using a mouse model of abdominal sepsis following intraperitoneal E. coli infection. The present work describes a targeted and effective sensing and antibacterial platform based on glycoconjugates that have potential applications for the treatment of infections caused by pathogenic microorganisms.
Keyphrases
- cancer therapy
- escherichia coli
- multidrug resistant
- drug delivery
- gram negative
- mouse model
- klebsiella pneumoniae
- ionic liquid
- intensive care unit
- machine learning
- single molecule
- acute kidney injury
- gene expression
- deep learning
- gold nanoparticles
- single cell
- genome wide
- binding protein
- silver nanoparticles
- pseudomonas aeruginosa