Establishment and Evaluation of a Core Genome Multilocus Sequence Typing Scheme for Whole-Genome Sequence-Based Typing of Pseudomonas aeruginosa.
Hauke TönniesKarola PriorDag HarmsenAlexander MellmannPublished in: Journal of clinical microbiology (2021)
The environmental bacterium Pseudomonas aeruginosa, particularly multidrug-resistant clones, is often associated with nosocomial infections and outbreaks. Today, core genome multilocus sequence typing (cgMLST) is frequently applied to delineate sporadic cases from nosocomial transmissions. However, until recently, no cgMLST scheme for a standardized typing of P. aeruginosa was available. To establish a novel cgMLST scheme for P. aeruginosa, we initially determined the breadth of the P. aeruginosa population based on MLST data with a Bayesian approach (BAPS). Using genomic data of representative isolates for the whole population and all 12 serogroups, we extracted target genes and further refined them using a random data set of 1,000 P. aeruginosa genomes. Subsequently, we investigated reproducibility and discriminatory ability with repeatedly sequenced isolates and isolates from well-defined outbreak scenarios, respectively, and compared clustering applying two recently published cgMLST schemes. BAPS generated seven P. aeruginosa groups. To cover these and all serogroups, 15 reference strains were used to determine genes common in all strains. After refinement with the data set of 1,000 genomes, the cgMLST scheme consisted of 3,867 target genes, which are representative of the P. aeruginosa population and highly reproducible using biological replicates. We finally evaluated the scheme by reanalyzing two published outbreaks where the authors used single-nucleotide polymorphism (SNP) typing. In both cases, cgMLST was concordant with the previous SNP results and the results of the two other cgMLST schemes. In conclusion, the highly reproducible novel P. aeruginosa cgMLST scheme facilitates outbreak investigations due to the publicly available cgMLST nomenclature.
Keyphrases
- genetic diversity
- genome wide
- pseudomonas aeruginosa
- acinetobacter baumannii
- electronic health record
- multidrug resistant
- big data
- visible light
- cystic fibrosis
- escherichia coli
- dna methylation
- drug resistant
- biofilm formation
- climate change
- systematic review
- gene expression
- risk assessment
- genome wide identification
- machine learning
- staphylococcus aureus
- gram negative
- single cell
- cross sectional
- early onset
- high density
- mass spectrometry
- amyotrophic lateral sclerosis
- candida albicans