Validation of Minim typing for fast and accurate discrimination of extended-spectrum, beta-lactamase-producing Klebsiella pneumoniae isolates in tertiary care hospital

Brhelová, Eva; Kocmanová, Iva; Ráčil, Zdeněk; Hanslianová, Markéta; Antonova, Mariya; Mayer, Jiřı́; Lengerová, Martina

doi:10.1016/j.diagmicrobio.2016.03.010

Cited by 7 publications

(7 citation statements)

References 27 publications

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“…We randomly selected 14 isolates from the four most predominant MelTs from 7/2016-5/2018 (3 MelT145 isolates, 5 MelT26 isolates, 3 MelT132 isolates and 3 MelT139 isolates). Because these MelTs were also present in our hospital during our previous study [14], we added 10 isolates isolated in our hospital in 2014 (3 MelT145 isolates, 1 MelT26 isolate, 3 MelT132 isolates and 3 MelT139 isolates).…”

Section: Resultsmentioning

confidence: 99%

“…In studies with a large number of samples, mini-MLST also can be used for sample sorting and pre-selecting for more detailed analysis. We evaluated this method for prospective ESBLp KPN population screening and to solve healthcare associated infection outbreaks in our previous study [14]. During the mini-MLST results evaluation, we were unable to determine the MelT of several isolates as their mini-MLST allele combination did not corresponded to any MelT in the published conversion key.…”

Section: Discussionmentioning

confidence: 99%

“…In order to evaluate the role of WGS in low diversity population outbreak analysis, we sequenced 46 ESBLp KPN isolates belonging to the four mostly spread MelTs from the monitored period from 7/2016 to 5/2018, isolates from the same MelTs originally collected for our mini-MLST pilot study in 2014 [14] and colonization/infection pair samples. First, we performed in silico MLST to correlate the STs with MelTs and characterise our population in the worldwide KPN population context.…”

Section: Discussionmentioning

confidence: 99%

“…In total, we collected 922 ESBLp KPN isolates (Table 1). For the purposes of this study, 24 ESBLp KPN isolates from our previous study collected between 1/2014 and 10/2014 were also included [14]. All isolates were collected during routine practice and were made completely anonymous.…”

Section: Methodsmentioning

confidence: 99%

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Application of mini-MLST and whole genome sequencing in low diversity hospital extended-spectrum beta-lactamase producing Klebsiella pneumoniae population

et al. 2019

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Studying bacterial population diversity is important to understand healthcare associated infections’ epidemiology and has a significant impact on dealing with multidrug resistant bacterial outbreaks. We characterised the extended-spectrum beta-lactamase producing K . pneumoniae (ESBLp KPN) population in our hospital using mini-MLST. Then we used whole genome sequencing (WGS) to compare selected isolates belonging to the most prevalent melting types (MelTs) and the colonization/infection pair isolates collected from one patient to study the ESBLp KPN population’s genetic diversity. A total of 922 ESBLp KPN isolates collected between 7/2016 and 5/2018 were divided into 38 MelTs using mini-MLST with only 6 MelTs forming 82.8% of all isolates. For WGS, 14 isolates from the most prominent MelTs collected in the monitored period and 10 isolates belonging to the same MelTs collected in our hospital in 2014 were randomly selected. Resistome, virulome and ST were MelT specific and stable over time. A maximum of 23 SNV per core genome and 58 SNV per core and accessory genome were found. To determine the SNV relatedness cut-off values, 22 isolates representing colonization/infection pair samples obtained from 11 different patients were analysed by WGS with a maximum of 22 SNV in the core genome and 40 SNV in the core and accessory genome within pairs. The mini-MLST showed its potential for real-time epidemiology in clinical practice. However, for outbreak evaluation in a low diversity bacterial population, mini-MLST should be combined with more sensitive methods like WGS. Our findings showed there were only minimal differences within the core and accessory genome in the low diversity hospital population and gene based SNV analysis does not have enough discriminatory power to differentiate isolate relatedness. Thus, intergenic regions and mobile elements should be incorporated into the analysis scheme to increase discriminatory power.

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Section: Resultsmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

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Application of mini-MLST and whole genome sequencing in low diversity hospital extended-spectrum beta-lactamase producing Klebsiella pneumoniae population

et al. 2019

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“…While some of the genotypic techniques utilize selected barcoding of parts of genomes, the others compare whole genomes. The first group mainly uses techniques for massive genotyping of pathogenic bacteria in epidemiologic studies and includes the utilization of electrophoresis, PCR, and amplicon sequencing [ [4] , [5] , [6] , [7] ]. The second group serves as a tool for the correct taxonomic placement of a new organism.…”

Section: Introductionmentioning

confidence: 99%

Rapid Bacterial Species Delineation Based on Parameters Derived From Genome Numerical Representations

Maderankova

Jugas

Sedlář

et al. 2019

Computational and Structural Biotechnology Journal

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Species delineation based on bacterial genomes is an essential part of the research of prokaryotes. In silico genome-to-genome comparison methods are computationally demanding, but much less tedious and error prone than the wet-lab methods. In this paper, we present a novel method for the delineation of bacterial genomes based on genomic signal processing. The proposed method uses numerical representations of whole bacterial genomes, phase signal and cumulated phase signal, from which four parameters are derived for each genome. The parameters characterize a genome and their calculation is independent of the other genomes comprising a delineation dataset. The delineation itself is processed as a calculation of the parameters' average similarity. The method was statistically verified on 1826 bacterial genomes. A similarity threshold of 96% was set based on the receiver operating characteristic curve that featured sensitivity of 99.78% and specificity of 97.25%. Additionally, comparative analysis on another 33 bacterial genomes was conducted using standard delineation tools as these tools were not able to process the dataset of 1826 genomes using desktop computer. The proposed method achieved comparable or better delineation results in comparison with the standard tools. Besides the excellent delineation results, another great advantage of the method is its small computational demands, which enables the delineation of thousands of genomes on a desktop computer. The calculation of the parameters takes tens of minutes for thousands of genomes. Moreover, they can be calculated in advance by creating a database, meaning the delineation itself is then completed in a matter of seconds.

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Entropy-Based Detection of Genetic Markers for Bacteria Genotyping

Nykrýnová

Maderankova

Barton

et al. 2019

Bioinformatics and Biomedical Engineering

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Validation of Minim typing for fast and accurate discrimination of extended-spectrum, beta-lactamase-producing Klebsiella pneumoniae isolates in tertiary care hospital

Cited by 7 publications

References 27 publications

Application of mini-MLST and whole genome sequencing in low diversity hospital extended-spectrum beta-lactamase producing Klebsiella pneumoniae population

Application of mini-MLST and whole genome sequencing in low diversity hospital extended-spectrum beta-lactamase producing Klebsiella pneumoniae population

Rapid Bacterial Species Delineation Based on Parameters Derived From Genome Numerical Representations

Entropy-Based Detection of Genetic Markers for Bacteria Genotyping

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