Genomic Epidemiology Dataset for the Important Nosocomial Pathogenic Bacterium Acinetobacter baumannii

Andrey Shelenkov (), Yulia Mikhaylova and Vasiliy Akimkin
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Andrey Shelenkov: Central Research Institute of Epidemiology, Novogireevskaya str., 3a, 111123 Moscow, Russia
Yulia Mikhaylova: Central Research Institute of Epidemiology, Novogireevskaya str., 3a, 111123 Moscow, Russia
Vasiliy Akimkin: Central Research Institute of Epidemiology, Novogireevskaya str., 3a, 111123 Moscow, Russia

Data, 2024, vol. 9, issue 2, 1-9

Abstract: The infections caused by various bacterial pathogens both in clinical and community settings represent a significant threat to public healthcare worldwide. The growing resistance to antimicrobial drugs acquired by bacterial species causing healthcare-associated infections has already become a life-threatening danger noticed by the World Health Organization. Several groups or lineages of bacterial isolates, usually called ‘the clones of high risk’, often drive the spread of resistance within particular species. Thus, it is vitally important to reveal and track the spread of such clones and the mechanisms by which they acquire antibiotic resistance and enhance their survival skills. Currently, the analysis of whole-genome sequences for bacterial isolates of interest is increasingly used for these purposes, including epidemiological surveillance and the development of spread prevention measures. However, the availability and uniformity of the data derived from genomic sequences often represent a bottleneck for such investigations. With this dataset, we present the results of a genomic epidemiology analysis of 17,546 genomes of a dangerous bacterial pathogen, Acinetobacter baumannii . Important typing information, including multilocus sequence typing (MLST)-based sequence types (STs), intrinsic bla OXA-51-like gene variants, capsular (KL) and oligosaccharide (OCL) types, CRISPR-Cas systems, and cgMLST profiles are presented, as well as the assignment of particular isolates to nine known international clones of high risk. The presence of antimicrobial resistance genes within the genomes is also reported. These data will be useful for researchers in the field of A. baumannii genomic epidemiology, resistance analysis, and prevention measure development.

Keywords: Acinetobacter baumannii; healthcare-associated infections; genomic epidemiology; whole-genome sequencing; cgMLST; international clones of high risk; antibiotic resistance (search for similar items in EconPapers)
JEL-codes: C8 C80 C81 C82 C83 (search for similar items in EconPapers)
Date: 2024
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