Lysozyme-encapsulated gold nanocluster-based affinity mass spectrometry for pathogenic bacteria

Abstract

Rationale: Bacterial infections can be difficult to treat and can lead to irreversible damage to patients if proper treatment is not provided in time. Additionally, the emerging threat from antibiotic-resistant bacterial strains makes medical treatment even more difficult. Thus, rapid identification of infected bacterial strains is essential to assist diagnostics and medical treatment.

Methods: Lysozymes are glycoside hydrolases that can bind with peptidoglycans on bacterial cell walls. In this work, we demonstrated that lysozyme-encapsulated gold nanoclusters (lysozyme-AuNCs) with red photoluminescence can be used as affinity probes to concentrate pathogenic bacteria. After bacteria had been probed by the lysozyme-AuNCs in a sample solution, the lysozyme-AuNC-bacteria conjugates were readily spun down at a low centrifugation speed. The red emission from the AuNCs on the conjugates could be visualized with the naked eye under illumination of ultraviolet light. The bacteria in the conjugates can be identified by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) combined with principal component analysis (PCA).

Results: We demonstrated that pathogenic bacteria including Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, pandrug-resistant Acinetobacter baumannii, Staphylococcus aureus, Enterococcus faecalis, and vancomycin-resistant Enterococcus faecalis (VRE) can be readily concentrated by the lysozyme-AuNCs and distinguished by the results combining MALDI-MS and PCA. Additionally, the possibility of using the current approach to differentiate E. faecalis from VRE was also demonstrated. The lowest detection concentration for E. coli using the current approach is ~10(6) cells/mL.

Conclusions: The results indicated that the lysozyme-AuNCs are effective affinity probes for Gram-positive and Gram-negative bacteria. By combining the results from MALDI-MS and PCA, different bacteria can be easily distinguished. The current approach can be potentially used to assist the identification of bacteria from biological fluids.