Generation of Synthetic Acinetobacter baumannii-Specific Nanobodies

Abstract

The bacterial pathogen Acinetobacter baumannii is a leading cause of drug-resistant infections. Here, we investigated the potential of developing nanobodies that can recognize A. baumannii over other Gram-negative bacteria. Through generation and panning of a synthetic nanobody library, we identified several potential lead candidates. We demonstrate how incorporation of next-generation sequencing analysis can aid in the selection of lead candidate nanobodies. Using monoclonal phage display, we validated the binding of lead nanobodies to A. baumannii. Subsequent purification and biochemical characterization revealed one particularly robust nanobody that specifically bound select A. baumannii strains compared to other common drug-resistant pathogens. These findings support the potential for nanobodies to selectively target A. baumannii and the identification of lead candidates for future investigation.