Shelenkov, A.; Mikhaylova, Y.; Akimkin, V. Genomic Epidemiology Dataset for the Important Nosocomial Pathogenic Bacterium Acinetobacter baumannii. Data2024, 9, 22.
Shelenkov, A.; Mikhaylova, Y.; Akimkin, V. Genomic Epidemiology Dataset for the Important Nosocomial Pathogenic Bacterium Acinetobacter baumannii. Data 2024, 9, 22.
Shelenkov, A.; Mikhaylova, Y.; Akimkin, V. Genomic Epidemiology Dataset for the Important Nosocomial Pathogenic Bacterium Acinetobacter baumannii. Data2024, 9, 22.
Shelenkov, A.; Mikhaylova, Y.; Akimkin, V. Genomic Epidemiology Dataset for the Important Nosocomial Pathogenic Bacterium Acinetobacter baumannii. Data 2024, 9, 22.
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 developing of spread prevention measures. However, the availability and uniformity of the data derived from the genomic sequences often represents a bottleneck for such investigations. In this dataset, we present the results of a comprehensive 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 blaOXA-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
Subject
Medicine and Pharmacology, Epidemiology and Infectious Diseases
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
