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

ProcaryaSV: structural variation detection pipeline for bacterial genomes using short-read sequencing

BACKGROUND

Structural variations play an important role in bacterial genomes. They can mediate genome adaptation quickly in response to the external environment and thus can also play a role in antibiotic resistance. The detection of structural variations in bacteria is challenging, and the recognition of even small rearrangements can be important. Even though most detection tools are aimed at and benchmarked on eukaryotic genomes, they can also be used on prokaryotic genomes. The key features of detection are the ability to detect small rearrangements and support haploid genomes. Because of the limiting performance of a single detection tool, combining the detection abilities of multiple tools can lead to more robust results. There are already available workflows for structural variation detection for long-reads technologies and for the detection of single-nucleotide variation and indels, both aimed at bacteria. Yet we are unaware of structural variations detection workflows for the short-reads sequencing platform. Motivated by this gap we created our workflow. Further, we were interested in increasing the detection performance and providing more robust results.

RESULTS

We developed an open-source bioinformatics pipeline, ProcaryaSV, for the detection of structural variations in bacterial isolates from paired-end short sequencing reads. Multiple tools, starting with quality control and trimming of sequencing data, alignment to the reference genome, and multiple structural variation detection tools, are integrated. All the partial results are then processed and merged with an in-house merging algorithm. Compared with a single detection approach, ProcaryaSV has improved detection performance and is a reproducible easy-to-use tool.

CONCLUSIONS

The ProcaryaSV pipeline provides an integrative approach to structural variation detection from paired-end next-generation sequencing of bacterial samples. It can be easily installed and used on Linux machines. It is publicly available on GitHub at https://github.com/robinjugas/ProcaryaSV .

Rapid Identification of Pseudomonas aeruginosa International High-Risk Clones Based on High-Resolution Melting Analysis

The Pseudomonas aeruginosa population has a nonclonal epidemic structure. It is generally composed of a limited number of widespread clones selected from a background of many rare and unrelated genotypes recombining at high frequency. Due to the increasing prevalence of nosocomial infections caused by multidrug-resistant/extensively drug-resistant (MDR/XDR) strains, it is advisable to implement infection control measures. Pulsed-field gel electrophoresis (PFGE) and multilocus sequence typing (MLST) are considered the gold standard methods in bacterial typing, despite being limited by cost, staff, and instrumental demands. Here, we present a novel mini-MLST scheme for P. aeruginosa rapid genotyping based on high-resolution melting analysis. Using the proposed mini-MLST scheme, 3,955 existing sequence types (STs) were converted into 701 melting types (MelTs), resulting in a discriminatory power of D = 0.993 (95% confidence interval [CI], 0.992 to 0.994). Whole-genome sequencing of 18 clinical isolates was performed to support the newly designed mini-MLST scheme. The clonal analysis of STs belonging to MelTs associated with international high-risk clones (HRCs) performed by goeBURST software revealed that a high proportion of the included STs are highly related to HRCs and have also been witnessed as responsible for serious infections. Therefore, mini-MLST provides a clear warning for the potential spread of P. aeruginosa clones recognized as MDR/XDR strains with possible serious outcomes. IMPORTANCE In this study, we designed a novel mini-MLST typing scheme for Pseudomonas aeruginosa. Its great discriminatory power, together with ease of performance and short processing time, makes this approach attractive for prospective typing of large isolate sets. Integrating the novel P. aeruginosa molecular typing scheme enables the development and spread of MDR/XDR high-risk clones to be investigated.

Identification of highly variable sequence fragments in unmapped reads for rapid bacterial genotyping

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.

PCR-based ORF typing of Klebsiella pneumoniae for rapid identification of global clones and transmission events

AIMS

Klebsiella pneumoniae is a major cause of healthcare-associated infections. In this study, we aimed to develop a rapid and simple genotyping method that can characterize strains causing nosocomial infections.

METHODS AND RESULTS

The PCR-based open reading frame (ORF) typing (POT) method consists of two multiplex PCR reactions which were designed to detect 25 ORFs specific to bacterial genetic lineages, species, antimicrobial resistant genes (bla_{CTX-M group-1} , bla_{CTX-M group-9} , bla_IMP and bla_KPC ), a capsular K1-specific gene, and a virulence factor gene (rmpA/A2). The electrophoresis results are then digitized. A total of 192 strains (136 clinical and 8 reference strains of K. pneumoniae, 33 clinical and 1 reference strains of K. variicola, and 14 clinical strains of K. quasipneumoniae) were classified into 95, 26, and 11 POT values, respectively. The distribution patterns of ORFs among K. pneumoniae correlated well with multilocus sequence typing (MLST). Furthermore, closely related species could be distinguished and key antimicrobial resistance and hypervirulence genes were identified as part of POT.

CONCLUSIONS

The POT method was developed and validated for K. pneumoniae. In comparison to MLST, the POT method is a rapid and easy genotyping method for monitoring transmission events by K. pneumoniae in clinical microbiology laboratories.

SIGNIFICANCE AND IMPACT OF THE STUDY

The POT method supplies clear and informative molecular typing results for K. pneumoniae. The method would facilitate molecular epidemiological analysis in infection control and hospital epidemiology investigations.

Sequencing Independent Molecular Typing of Staphylococcus aureus Isolates: Approach for Infection Control and Clonal Characterization

Staphylococcus aureus is a major bacterial human pathogen that causes a wide variety of clinical manifestations. The main aim of the presented study was to determine and optimize a novel sequencing independent approach that enables molecular typing of S. aureus isolates and elucidates the transmission of emergent clones between patients. In total, 987 S. aureus isolates including both methicillin-resistant S. aureus (MRSA) and methicillin-sensitive S. aureus (MSSA) isolates were used to evaluate the novel typing approach combining high-resolution melting (HRM) analysis of multilocus sequence typing (MLST) genes (mini-MLST) and spa gene (spa-HRM). The novel approach's discriminatory ability was evaluated by whole-genome sequencing (WGS). The clonal relatedness of tested isolates was set by the BURP and BURST approach using spa and MLST data, respectively. Mini-MLST classified the S. aureus isolates into 38 clusters, followed by spa-HRM classifying the isolates into 101 clusters. The WGS proved HRM-based methods to effectively differentiate between related S. aureus isolates. Visualizing evolutionary relationships among different spa-types provided by the BURP algorithm showed comparable results to MLST/mini-MLST clonal clusters. We proved that the combination of mini-MLST and spa-HRM is rapid, reproducible, and cost-efficient. In addition to high discriminatory ability, the correlation between spa evolutionary relationships and mini-MLST clustering allows the variability in population structure to be monitored. IMPORTANCE Rapid and cost-effective molecular typing tools for Staphylococcus aureus epidemiological applications such as transmission tracking, source attribution and outbreak investigations are highly desirable. High-resolution melting based methods are effective alternative to those based on sequencing. Their good reproducibility and easy performance allow prospective typing of large set of isolates while reaching great discriminatory power. In this study, we established a new epidemiological approach to S. aureus typing. This scheme has the potential to greatly improve epidemiological investigations of S. aureus.

CNproScan: Hybrid CNV detection for bacterial genomes

Discovering copy number variation (CNV) in bacteria is not in the spotlight compared to the attention focused on CNV detection in eukaryotes. However, challenges arising from bacterial drug resistance bring further interest to the topic of CNV and its role in drug resistance. General CNV detection methods do not consider bacteria's features and there is space to improve detection accuracy. Here, we present a CNV detection method called CNproScan focused on bacterial genomes. CNproScan implements a hybrid approach and other bacteria-focused features and depends only on NGS data. We benchmarked our method and compared it to the previously published methods and we can resolve to achieve a higher detection rate together with providing other beneficial features, such as CNV classification. Compared with other methods, CNproScan can detect much shorter CNV events.

Word Entropy-Based Approach to Detect Highly Variable Genetic Markers for Bacterial Genotyping

Genotyping methods are used to distinguish bacterial strains from one species. Thus, distinguishing bacterial strains on a global scale, between countries or local districts in one country is possible. However, the highly selected bacterial populations (e.g., local populations in hospital) are typically closely related and low diversified. Therefore, currently used typing methods are not able to distinguish individual strains from each other. Here, we present a novel pipeline to detect highly variable genetic segments for genotyping a closely related bacterial population. The method is based on a degree of disorder in analyzed sequences that can be represented by sequence entropy. With the identified variable sequences, it is possible to find out transmission routes and sources of highly virulent and multiresistant strains. The proposed method can be used for any bacterial population, and due to its whole genome range, also non-coding regions are examined.

Concordance between epidemiological evaluation of probability of transmission and whole genome sequence relatedness among hospitalized patients acquiring Klebsiella pneumoniae carbapenemase-producing Klebsiella pneumoniae

OBJECTIVES

We aimed to evaluate the concordance between epidemiologically determined transmission and genetic linkage of Klebsiella pneumoniae carbapenemase (KPC)-producing Klebsiella pneumoniae (KPC-Kp).

METHODS

We included consecutive KPC-Kp carriers between December 2016 and April 2017 in a hospital endemic for KPC-Kp. We assessed epidemiological relatedness between patients by prospective investigations by the infection control team. The probability of epidemiological relatedness was classified into four groups: no suspected transmission, low, moderate and high probability of transmission. Whole-genome sequencing of isolates was performed. Genetic linkage between KPC-Kp isolates was expressed by distance between isolates in single nucleotide polymorphisms (SNPs). We established an SNP cut-off defining a different strain based on the reconstructed phylogenetic tree. We compared the epidemiological and genetic linkage of all isolates from all patients.

RESULTS

The study included 25 KPC-Kp carriers with 49 isolates. SNP variance was available for 1129 crossed patient-isolate pairs. Genomic linkage, based on a cut-off of 80 SNPs to define related isolates, was found in 115/708 (16.2%) of isolates with no transmission suspected epidemiologically, 27/319 (8.5%) of low, 11/26 (42.3%) of moderate and 64/76 (84.2%) of high epidemiological transmission risk determination (p < 0.001 for trend). Similar results and significant trends were shown on sensitivity analyses using a lower SNP cut-off (six SNPs) and patient-isolate unique pairs, analysing the first isolate from each patient.

CONCLUSIONS

While significant concordance between epidemiological and genomic transmission patterns was found, epidemiological investigations of transmission are limited by the possibility of unidentified transmissions or over-estimation of associations. Genetic linkage analysis is an important aid to epidemiological transmission assessment.

Current strategy for local- to global-level molecular epidemiological characterisation of global antimicrobial resistance surveillance system pathogens

The prime goal of molecular epidemiology is to identify the origin and evolution of pathogens, which can potentially influence the public health worldwide. Traditional methods provide limited information which is not sufficient for outbreak investigation and studying transmission dynamics. The recent advancement of next-generation sequencing had a major impact on molecular epidemiological studies. Currently, whole-genome sequencing (WGS) has become the gold standard typing method, especially for clinically significant pathogens. Here, we aimed to describe the application of appropriate molecular typing methods for global antimicrobial resistance surveillance system pathogens based on the level of discrimination and epidemiological settings. This shows that sequence-based methods such as multi-locus sequence typing (MLST) are widely used due to cost-effectiveness and database accessibility. However, WGS is the only method of choice for studying Escherichia coli and Shigella spp. WGS is shown to have higher discrimination than other methods in typing Klebsiella pneumoniae, Acinetobacter baumannii and Salmonella spp. due to its changing accessory genome content. For Gram positives such as Streptococcus pneumoniae, WGS would be preferable to understand the evolution of the strains. Similarly, for Staphylococcus aureus, combination of MLST, staphylococcal protein A or SCCmec typing along with WGS could be the choice for epidemiological typing of hospital- and community-acquired strains. This review highlights that combinations of different typing methods should be used to get complete information since no one standalone method is sufficient to study the varying genome diversity.