Fluorescence-based detection of natural transformation in drug resistant Acinetobacter baumannii

Abstract

Acinetobacter baumannii is a nosocomial agent with a high propensity for developing resistance to antibiotics. This ability relies on horizontal gene transfer mechanisms occurring in the Acinetobacter genus, including natural transformation. To study natural transformation in bacteria, the most prevalent method uses selection for the acquisition of an antibiotic resistance marker in a target chromosomal locus by the recipient cell. Most clinical isolates of A. baumannii are resistant to multiple antibiotics limiting the use of such selection-based method. Here we report the development of a phenotypic and selection-free method based on flow cytometry to detect transformation events in multidrug resistant (MDR) clinical A. baumannii isolates. To this end, we engineered a translational fusion between the abundant and conserved A. baumannii nucleoprotein (HU) and the superfolder green fluorescent protein (sfGFP). The new method was benchmarked against the conventional antibiotic selection-based method. Using this new method, we investigated several parameters affecting transformation efficiencies and identified conditions of transformability one hundred times higher than those previously reported. Using optimized transformation conditions, we probed natural transformation in a set of MDR clinical and non-clinical animal A. baumannii isolates. Regardless of their origin, the majority of the isolates displayed natural transformability, indicative of a conserved trait in the species. Overall, this new method and optimized protocol will greatly facilitate the study of natural transformation in the opportunistic pathogen A. baumannii.