Rapid species differentiation and typing of Acinetobacter baumannii

Acinetobacter (A.) baumannii has emerged as a difficult-to-treat nosocomial bacterial human pathogen. A. baumannii is to be dealt with under the “One Health” approach, and its surveillance in human, animal, and environmental settings assumes paramount importance in understanding its plausible transmission dynamics. Accurate identification of A. baumannii, its clonal complexes, and sequence types is important for understanding the epidemiological distribution, evolutionary relationships, and transmission dynamics. A wide range of genotyping techniques are applied for the differentiation of the Acinetobacter calcoaceticus-baumannii (ACB) complex. However, there is no single straight-forward genotype method applied for rapid assays. Currently, two multilocus sequence typing (MLST) Oxford and Pasture schemes exist; though considered a gold standard for sequence typing, harmonizing the schemes is not a straightforward process. The whole genome sequencing-based core-genome multilocus sequence typing (cgMLST) and core single nucleotide polymorphism (cgSNP) are robust and precise sequence typing; however, they are expensive, depending on the quality of sequencing and demand a higher level of computational skills. In the past decade, matrix-assisted laser desorption ionization-time of flight mass spectrometry (MALDI-TOF MS) based species identification has been successfully employed for rapid discrimination of the ACB complex. MALDI typing is rapid, easier, cheaper, and as reliable as molecular methods. Strain level A. baumannii identification confidence improved upon augmentation of existing databases with in-house reference spectra of well-defined isolates. The application of artificial intelligence and machine learning might be useful in clonal sequence types (ST)-level identification. The genus Acinetobacter’s taxonomic classification is evolving, and newer STs are being described; hence, the establishment of a central repository of A. baumannii reference spectra will help in harmonizing across the laboratories and help in the global level surveillance program on A. baumannii in “One Health” perspective. This review sheds light on the challenges related to techniques employed for the identification of Acinetobacter and the potential application and future perspectives of MALDI-TOF MS.