Accessory Genomic Epidemiology of Cocirculating Acinetobacter baumannii Clones

Acinetobacter baumannii has become one of the most important multidrug-resistant nosocomial pathogens all over the world. Nonetheless, very little is known about the diversity of A. baumannii lineages coexisting in hospital settings. Here, using whole-genome sequencing, epidemiological data, and antimicrobial susceptibility tests, we uncover the transmission dynamics of extensive and multidrug-resistant A. baumannii in a tertiary hospital over a decade. Our core genome phylogeny of almost 300 genomes suggests that there were several introductions of lineages from international clone 2 into the hospital. The molecular dating analysis shows that these introductions happened in 2006, 2007, and 2013. Furthermore, using the accessory genome, we show that these lineages were extensively disseminated across many wards in the hospital. Our results demonstrate that accessory genome variation can be a very powerful tool for conducting genomic epidemiology. We anticipate future studies employing the accessory genome along with the core genome as a powerful phylogenomic strategy to track bacterial transmissions over very short microevolutionary scales. Whole-genome sequencing for epidemiological investigations (genomic epidemiology) has been of paramount importance to understand the transmission dynamics of many bacterial (and nonbacterial) pathogens. Commonly, variation in the core genome, single nucleotide polymorphisms (SNPs), is employed to carry out genomic epidemiology. However, at very short periods of time, the core genome might not have accumulated enough variation (sufficient SNPs) to tell apart isolates. In this scenario, gene content variation in the accessory genome can be an option to conduct genomic epidemiology. Here, we used the accessory genome, as well as the core genome, to uncover the transmission dynamics of extensive and multidrug-resistant A. baumannii in a tertiary hospital for a decade. Our study shows that accessory genome variation can be a very powerful tool for conducting genomic epidemiology.