ArticleMicrobiology spectrum2022
Core Genome Multilocus Sequence Typing and Antibiotic Susceptibility Prediction from Whole-Genome Sequence Data of Multidrug-Resistant Pseudomonas aeruginosa Isolates.
Article in Microbiology spectrum, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 6 citations in OpenAlex.
- Applicability of Nanopore-only whole-genome sequencing forJournal of clinical microbiology · 2026Article
- Understanding recurrence inJournal of clinical microbiology · 2026Review
- Genomic and epidemiological identification of Pseudomonas aeruginosa transmission chains and in hospital ICUs.Genome biology · 2026Article
- Multidrug-resistant gram-negative bacteria in Spanish ICU patients: clinical and microbiological characterization (MURAN-UCI Project).Microbiology spectrum · 2026Article
- High genetic relatedness between multidrug resistant bacteria before and after the 2022 invasion of Ukraine.Genome medicine · 2025Article
- Automated whole genome sequencing platform for bacterial strain typing in clinical microbiology laboratories.Journal of clinical microbiology · 2025Article
- Direct prediction of carbapenem resistance inJournal of clinical microbiology · 2023Article
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Authors and funding
6 authors at 1 institution in 1 country.
Funding
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Abstract
Over the past decade, whole-genome sequencing (WGS) has overtaken traditional bacterial typing methods for studies of genetic relatedness. Further, WGS data generated during epidemiologic studies can be used in other clinically relevant bioinformatic applications, such as antibiotic resistance prediction. Using commercially available software tools, the relatedness of 38 clinical isolates of multidrug-resistant Pseudomonas aeruginosa was defined by two core genome multilocus sequence typing (cgMLST) methods, and the WGS data of each isolate was analyzed to predict antibiotic susceptibility to nine antibacterial agents. The WGS typing and resistance prediction data were compared with pulsed-field gel electrophoresis (PFGE) and phenotypic antibiotic susceptibility results, respectively. Simpson's Diversity Index and adjusted Wallace pairwise assessments of the three typing methods showed nearly identical discriminatory power. Antibiotic resistance prediction using a trained analytical pipeline examined 342 bacterial-drug combinations with an overall categorical agreement of 92.4% and very major, major, and minor error rates of 3.6, 4.1, and 4.1%, respectively.
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