BACKGROUND: Bacterial genotyping is a crucial process in outbreak investigation and epidemiological studies. Several typing methods such as pulsed-field gel electrophoresis, multilocus sequence typing (MLST) and whole genome sequencing are currently used in routine clinical practice. However, these methods are costly, time-consuming and have high computational demands. An alternative to these methods is mini-MLST, a quick, cost-effective and robust method based on high-resolution melting analysis. Nevertheless, no standardized approach to identify markers suitable for mini-MLST exists. Here, we present a pipeline for variable fragment detection in unmapped reads based on a modified hybrid assembly approach using data from one sequencing platform. RESULTS: In routine assembly against the reference sequence, high variable reads are not aligned and remain unmapped. If de novo assembly of them is performed, variable genomic regions can be located in created scaffolds. Based on the variability rates calculation, it is possible to find a highly variable region with the same discriminatory power as seven housekeeping gene fragments used in MLST. In the work presented here, we show the capability of identifying one variable fragment in de novo assembled scaffolds of 21 Escherichia coli genomes and three variable regions in scaffolds of 31 Klebsiella pneumoniae genomes. For each identified fragment, the melting temperatures are calculated based on the nearest neighbor method to verify the mini-MLST's discriminatory power. CONCLUSIONS: A pipeline for a modified hybrid assembly approach consisting of reference-based mapping and de novo assembly of unmapped reads is presented. This approach can be employed for the identification of highly variable genomic fragments in unmapped reads. The identified variable regions can then be used in efficient laboratory methods for bacterial typing such as mini-MLST with high discriminatory power, fully replacing expensive methods such as MLST. The results can and will be delivered in a shorter time, which allows immediate and fast infection monitoring in clinical practice.

• Klíčová slova
• Bacterial genotyping, De novo assembly, Genome assembly, Mini-MLST, Multilocus sequence typing, Unmapped reads,
• MeSH
• Bacteria * genetika   MeSH
• Escherichia coli genetika   MeSH
• genom * MeSH
• genotyp MeSH
• multilokusová sekvenční typizace metody   MeSH
• techniky typizace bakterií metody   MeSH
• Publikační typ
• časopisecké články MeSH

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.

• MeSH
• bakteriální proteiny genetika   MeSH
• beta-laktamasy genetika   metabolismus   MeSH
• dítě MeSH
• DNA bakterií genetika   MeSH
• dospělí MeSH
• infekce bakteriemi rodu Klebsiella enzymologie   epidemiologie   genetika   mikrobiologie   MeSH
• infekce spojené se zdravotní péčí enzymologie   epidemiologie   genetika   mikrobiologie   MeSH
• Klebsiella pneumoniae enzymologie   genetika   izolace a purifikace   MeSH
• kojenec MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mnohočetná bakteriální léková rezistence * MeSH
• multilokusová sekvenční typizace * MeSH
• novorozenec MeSH
• předškolní dítě MeSH
• sekvenování celého genomu * MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• Check Tag
• dítě MeSH
• dospělí MeSH
• kojenec MeSH
• lidé středního věku MeSH
• lidé MeSH
• mladiství MeSH
• mužské pohlaví MeSH
• novorozenec MeSH
• předškolní dítě MeSH
• senioři nad 80 let MeSH
• senioři MeSH
• ženské pohlaví MeSH
• Publikační typ
• časopisecké články MeSH
• práce podpořená grantem MeSH
• Názvy látek
• bakteriální proteiny MeSH
• beta-laktamasy MeSH
• DNA bakterií MeSH

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.

• Klíčová slova
• Bacterial genome, Comparative genomics, Genomic signal processing, Numerical representation, Species delineation,
• Publikační typ
• časopisecké články MeSH