Analytical Chemistry · 2022 · 29 citations · 26 references
Life SciencesInfectious DiseasesMicrobiologyBacteriologyBiosensorsProtein EngineeringBacterial IdentificationClinical BacteriologyDiagnostic BacteriologyPathogen DetectionPhage DisplayPhage GeneticsBacterial DetectionBacterial Surface ReceptorsLytic BacteriophagesMolecular Detection AssaysMolecular Detection Of BacteriaMultidrug-resistant PathogensPhage-based DetectionSpecies-specific Protein Recognition
As a multidrug-resistant pathogen, Acinetobacter baumannii has long been identified as one of the most common nosocomial bacteria. High-performance recognition probes for wide-spectrum detection of A. baumannii are highly desired to achieve efficient diagnosis and timely treatment of infectious diseases induced by this pathogen. An engineering tail fiber protein (ETFP) named as Gp50 encoded by lytic phage Abp9 was expressed in Escherichia coli and identified as a binding protein for A. baumannii. According to the results of genome sequencing of an A. baumannii wild strain and phage-resistant strains, the binding receptor of ETFP Gp50 is inferred to be a lipopolysaccharide distributed on the bacterial surface. The engineering protein did not show lytic activity to A. baumannii, which facilitates the development of reliable diagnosis kits and biosensors with high flexibility and low false-negative rate. The results of specificity study show that ETFP Gp50 is a species-specific binding protein with a recognition rate of 100% for all tested 77 A. baumannii strains, while that of the natural phage Abp9 is only 27.3%. With the engineering protein, a fluorescence method was developed to detect A. baumannii with a detection range of 2.0 × 102 to 2.0 × 108 cfu mL–1. The method has been used for the quantification of A. baumannii in a diverse sample matrix with acceptable reliability. The work demonstrates the application potential of ETFP Gp50 as an ideal recognition probe for rapid screening of A. baumannii strains in a complicated sample matrix.
26
Nonhybrid, finished microbial genome assemblies from long-read SMRT sequencing data
Chen-Shan Chin, David H. Alexander, Patrick Marks et al. · Nature Methods · 2013 · 4.3K citations
Robert T. Schooley, Biswajit Biswas, Jason J. Gill et al. · Antimicrobial Agents and Chemotherapy · 2017 · 1.3K citations · Full text