Multi-screening of beta-lactam antibiotics in milk based on Fe3O4@phage/bacteria system and aggregation induced emission luminogen.
TL;DR
This is the first study reporting the use of phage/bacterium system and aggregation induced emission luminogen for detection of antibiotic residues in food sample.
Abstract
Background
For the previous rapid screening methods, antibody, molecularly imprinted polymer, aptamer and receptor are the usually used recognition reagents. It is well known that there are many antibiotic receptors on bacterial surface, so in theory the whole bacterium can be used as recognition reagent for screening of the specific antibiotic. However, such a method has not been reported so far. The aim of the present study is to develop a method for rapid screening of beta-lactam drugs in milk with Escherichia coli as the recognition reagent and with aggregation induced emission luminogen as the signal source.
Results
In this study, T4 phage was coupled with Fe3O4 to synthesize a type of magnetic complex that could specifically capture E. coli. Cephalexin was coupled with an aggregation induced emission luminogen (tetraphenylethylene) to synthesize a fluorescent tracer that could specifically bind with the penicillin binding proteins on E. coli surface. The magnetic complex, the E. coli solution and the tracer were mixed with beta-lactam drugs to perform competition. The fluorescent signal from the tracer molecules aggregated on bacterial surface was negatively correlated with the drug concentration. This method could be used for multi-screening of 28 beta-lactam drugs. The operation was simple and rapid, and the sensitivities for these drugs (limits of detection of 0.73-95.19 pg/mL) were improved for 16-959 folds in comparison with fluorescein based fluorescent tracer. The detection results for the real milk samples were consistent with a LC-MS/MS method.
Significance
This is the first study reporting the use of phage/bacterium system and aggregation induced emission luminogen for detection of antibiotic residues in food sample. Under the guidance of this study, more similar or advanced methods based on bacteria and novel signal sources for detection of antibiotics should be reported in the future.
