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Detection of Bacteria Using Fluorogenic DNAzymes
Published on: May 28, 2012
Phage-induced "one-to-many" FRET sensor for highly sensitive detection of Escherichia coli O157:H7
Meng Meng1, Xiaoyong Ma1, Liping Yu1
1Hunan Key Laboratory of Forestry Edible Resources Safety and Processing, National Engineering Research Center of Rice and Byproducts Deep Processing, College of Food Science and Engineering, Central South University of Forestry and Technology, Changsha, Hunan, 410004, China.
Abstract:
As a foodborne pathogen capable of causing severe illnesses, early detection of Escherichia coli O157:H7 (E. coli O157:H7) is crucial for ensuring food safety. While Förster resonance energy transfer (FRET) is an efficient and precise detection technique, there remains a need for amplification strategies to detect low concentrations of E. coli O157:H7. In this study, we presented a phage (M13)-induced "one to many" FRET platform for sensitively detecting E. coli O157:H7. The aptamers, which specifically recognize E. coli O157:H7 were attached to magnetic beads as capture probes for separating E. coli O157:H7 from food samples. The peptide O157S, which specifically targets E. coli O157:H7, and streptavidin binding peptide (SBP), which binds to streptavidin (SA), were displayed on the P3 and P8 proteins of M13, respectively, to construct the O157S-M13K07-SBP phage as a detection probe for signal output. Due to the precise distance (≈3.2 nm) between two neighboring N-terminus of P8 protein, the SA-labeled FRET donor and acceptor can be fixed at the Förster distance on the surface of O157S-M13K07-SBP via the binding of SA and SBP, inducing FRET. Moreover, the P8 protein, with ≈2700 copies, enabled multiple FRET (≈605) occurrences, amplifying FRET in each E. coli O157:H7 recognition event. The O157S-M13K07-SBP-based FRET sensor can detect E. coli O157:H7 at concentration as low as 6 CFU/mL and demonstrates excellent performance in terms of selectivity, detection time (≈3 h), accuracy, precision, practical application, and storage stability. In summary, we have developed a powerful tool for detecting various targets in food safety, environmental monitoring, and medical diagnosis.

