Split k-mer analysis compared to cgMLST and SNP-based core genome analysis for detecting transmission of vancomycin-resistant enterococci: results from routine outbreak analyses across different hospitals and hospitals networks in Berlin, Germany

Co-carriage of diverse vancomycin-resistant Enterococcus faecium ST80-lineages by 70% of patients in an Irish hospital

Background

Vancomycin-resistant Enterococcus faecium (VREfm) are significant nosocomial pathogens. Irish VREfm comprise diverse vanA-encoding ST80-complex type (CT) lineages. Recent studies indicate that within-patient VREfm diversity could confound surveillance. This study investigated the intra-host VREfm genetic diversity among colonized Irish hospital patients.

Methods

Rectal VREfm (n = 150) from 10 patients (15 isolates each) were investigated by WGS, core-genome MLST and split k-mer (SKA)-SNP analysis. Plasmids and vanA-transposons from 39 VREfm representative of CTs identified were resolved by hybrid assembly of short-read (Illumina) and long-read (Oxford Nanopore Technologies) sequences. Plasmid relatedness was assessed based on Mash distances. Thirty vancomycin-susceptible E. faecium (VSEfm) from four VREfm-positive patients were also investigated.

Results

All isolates were clade A1 and most were ST80 (VREfm, 147/150; VSEfm, 25/30). Seventy-percent of patients (7/10) harboured either two (n = 4), three (n = 2) or four (n = 1) VREfm CTs. Individual patient isolate pairs from different CTs differed significantly (median SKA-SNPs 2933), but differences were minimal between isolate pairs of the same CT (median SKA-SNPs 0). In total, 193 plasmids were identified in 39 VREfm investigated. Near-identical plasmids (≥99.5% average nucleotide identity) were identified in divergent CTs from multiple patients. Most VREfm (28/39, 72%) harboured vanA on closely related transferable, linear plasmids. Divergent CTs within individual patients harboured either indistinguishable vanA-transposons or vanA-transposons with distinct organizational iterations. Four VSEfm from different CTs investigated harboured similar plasmids to VREfm.

Conclusion

VREfm within-host diversity is highly prevalent in Irish hospital patients, which complicates surveillance. Linear plasmids play an important role in the emergence of Irish VREfm.

Reference-Free Variant Calling with Local Graph Construction with ska lo (SKA)

The study of genomic variants is increasingly important for public health surveillance of pathogens. Traditional variant-calling methods from whole-genome sequencing data rely on reference-based alignment, which can introduce biases and require significant computational resources. Alignment- and reference-free approaches offer an alternative by leveraging k-mer-based methods, but existing implementations often suffer from sensitivity limitations, particularly in high mutation density genomic regions. Here, we present ska lo, a graph-based algorithm that aims to identify within-strain variants in pathogen whole-genome sequencing data by traversing a colored De Bruijn graph and building variant groups (i.e. sets of variant combinations). Through in silico benchmarking and real-world dataset analyses, we demonstrate that ska lo achieves high sensitivity in single-nucleotide polymorphism (SNP) calls while also enabling the detection of insertions and deletions, as well as SNP positioning on a reference genome for recombination analyses. These findings highlight ska lo as a simple, fast, and effective tool for pathogen genomic epidemiology, extending the range of reference-free variant-calling approaches. ska lo is freely available as part of the SKA program (https://github.com/bacpop/ska.rust).

Integrated population clustering and genomic epidemiology with PopPIPE

Genetic distances between bacterial DNA sequences can be used to cluster populations into closely related subpopulations and as an additional source of information when detecting possible transmission events. Due to their variable gene content and order, reference-free methods offer more sensitive detection of genetic differences, especially among closely related samples found in outbreaks. However, across longer genetic distances, frequent recombination can make calculation and interpretation of these differences more challenging, requiring significant bioinformatic expertise and manual intervention during the analysis process. Here, we present a Population analysis PIPEline (PopPIPE) which combines rapid reference-free genome analysis methods to analyse bacterial genomes across these two scales, splitting whole populations into subclusters and detecting plausible transmission events within closely related clusters. We use k-mer sketching to split populations into strains, followed by split k-mer analysis and recombination removal to create alignments and subclusters within these strains. We first show that this approach creates high-quality subclusters on a population-wide dataset of Streptococcus pneumoniae. When applied to nosocomial vancomycin-resistant Enterococcus faecium samples, PopPIPE finds transmission clusters that are more epidemiologically plausible than core genome or multilocus sequence typing (MLST) approaches. Our pipeline is rapid and reproducible, creates interactive visualizations and can easily be reconfigured and re-run on new datasets. Therefore, PopPIPE provides a user-friendly pipeline for analyses spanning species-wide clustering to outbreak investigations.

Bacteriocin production facilitates nosocomial emergence of vancomycin-resistant Enterococcus faecium

Gastrointestinal colonization by the nosocomial pathogen vancomycin-resistant Enterococcus faecium (VREfm) can lead to bloodstream infections with high mortality rates. Shifts in VREfm lineages found within healthcare settings occur, but reasons underlying these changes are not understood. Here we sequenced 710 VREfm clinical isolates collected between 2017 and 2022 from a large tertiary care centre. Genomic analyses revealed a polyclonal VREfm population, although 46% of isolates formed genetically related clusters, suggesting a high transmission rate. Comparing these data to a global collection of 15,631 publicly available VREfm genomes collected between 2002 and 2022 identified replacement of the sequence type (ST) 17 VREfm lineage by emergent ST80 and ST117 lineages at the local and global level. Comparative genomic and functional analyses revealed that emergent lineages encoded bacteriocin T8, which conferred a competitive advantage over bacteriocin T8-negative strains in vitro and upon colonization of the mouse gut. Bacteriocin T8 carriage was also strongly associated with strain emergence in the global genome collection. These data suggest that bacteriocin T8-mediated competition may have contributed to VREfm lineage replacement.

Rapid, reference-free identification of bacterial pathogen transmission using optimized split k-mer analysis

Infections caused by multidrug-resistant organisms (MDROs) are difficult to treat and often life threatening and place a burden on the healthcare system. Minimizing the transmission of MDROs in hospitals is a global priority with genomics proving to be a powerful tool for identifying the transmission of MDROs. To optimize the utility of genomics for prospective infection control surveillance, results must be available in real time, reproducible and simple to communicate to clinicians. Traditional reference-based approaches suffer from several limitations for prospective genomic surveillance. Whilst reference-free or pairwise genome comparisons avoid some of these limitations, they can be computationally intensive and time consuming. Split k-mer analysis (SKA) offers a viable alternative facilitating rapid reference-free pairwise comparisons of genomic data, but the optimum SKA parameters for the detection of transmission have not been determined. Additionally, the accuracy of SKA-based inferences has not been measured, nor whether modified quality control parameters are required. Here, we explore the performance of 60 SKA parameter combinations across 50 simulations to quantify the false negative and positive SNP proportions for Escherichia coli, Enterococcus faecium, Klebsiella pneumoniae and Staphylococcus aureus. Using the optimum parameter combination, we explore concordance between SKA, multilocus sequence typing (MLST), core genome MLST (cgMLST) and Snippy in a real-world dataset. Lastly, we investigate whether simulated plasmid gain or loss could impact SNP detection with SKA. This work identifies that the use of SKA with sequencing reads, a k-mer length of 19 and a minor allele frequency filter of 0.01 is optimal for MDRO transmission detection. Whilst SNP detection with SKA (when used with sequencing reads) undercalls SNPs compared to Snippy, it is significantly faster, especially with larger datasets. SKA has excellent concordance with MLST and cgMLST and is not impacted by simulated plasmid movement. We propose that the use of SKA for the detection of bacterial pathogen transmission is superior to traditional methodologies, capable of providing results in a much shorter timeframe.

Seamless, rapid, and accurate analyses of outbreak genomic data using split k-mer analysis

Sequence variation observed in populations of pathogens can be used for important public health and evolutionary genomic analyses, especially outbreak analysis and transmission reconstruction. Identifying this variation is typically achieved by aligning sequence reads to a reference genome, but this approach is susceptible to reference biases and requires careful filtering of called genotypes. There is a need for tools that can process this growing volume of bacterial genome data, providing rapid results, but that remain simple so they can be used without highly trained bioinformaticians, expensive data analysis, and long-term storage and processing of large files. Here we describe split k-mer analysis (SKA2), a method that supports both reference-free and reference-based mapping to quickly and accurately genotype populations of bacteria using sequencing reads or genome assemblies. SKA2 is highly accurate for closely related samples, and in outbreak simulations, we show superior variant recall compared with reference-based methods, with no false positives. SKA2 can also accurately map variants to a reference and be used with recombination detection methods to rapidly reconstruct vertical evolutionary history. SKA2 is many times faster than comparable methods and can be used to add new genomes to an existing call set, allowing sequential use without the need to reanalyze entire collections. With an inherent absence of reference bias, high accuracy, and a robust implementation, SKA2 has the potential to become the tool of choice for genotyping bacteria. SKA2 is implemented in Rust and is freely available as open-source software.

The genetic relationship between human and pet isolates: a core genome multilocus sequence analysis of multidrug-resistant bacteria

INTRODUCTION

The global increase of multidrug-resistant organisms (MDROs) is one of the most urgent public health threats affecting both humans and animals. The One Health concept emphasizes the interconnectedness of human, animal and environmental health and highlights the need for integrated approaches to combat antimicrobial resistance (AMR). Although the sharing of environments and antimicrobial agents between companion animals and humans poses a risk for MDRO transmission, companion animals have been studied to a lesser extent than livestock animals. This study therefore used core genome multilocus sequence typing (cgMLST) to investigate the genetic relationships and putative transmission of MDROs between humans and pets.

METHODS

This descriptive integrated typing study included 252 human isolates, 53 dog isolates and 10 cat isolates collected from 2019 to 2022 at the Charité University Hospital in Berlin, Germany. CgMLST was performed to characterize methicillin-resistant Staphylococcus aureus, vancomycin-resistant enterococci and multidrug-resistant gram-negative bacteria. The genetic diversity of the MDROs of the different host populations was determined and compared based on sequence type and core genome complex type.

RESULTS

Within this study the majority of samples from pets and humans was genetically distinct. However, for some isolates, the number of allelic differences identified by cgMLST was low. Two cases of putative household transmission or shared source of VR E. faecium and MDR E. coli between humans and pets were documented.

CONCLUSIONS

The interaction between humans and their pets appears to play a minor role in the spread of the MDROs studied. However, further research is needed. This study emphasizes the importance of comprehensive molecular surveillance and a multidisciplinary One Health approach to understand and contain the spread of MDROs in human and animal populations.

TRIAL REGISTRATION

The study is registered with the German Clinical Trials Register (DRKS00030009).

Genomic insights into the antimicrobial resistance and virulence of Helicobacter pylori isolates from gastritis patients in Pereira, Colombia

BACKGROUND

Helicobacter pylori infects the stomach and/or small intestines in more than half of the human population. Infection with H. pylori is the most common cause of chronic gastritis, which can lead to more severe gastroduodenal pathologies such as peptic ulcer, mucosa-associated lymphoid tissue lymphoma, and gastric cancer. H. pylori infection is particularly concerning in Colombia in South America, where > 80% of the population is estimated to be infected with H. pylori and the rate of stomach cancer is one of the highest in the continent.

RESULTS

We compared the antimicrobial susceptibility profiles and short-read genome sequences of five H. pylori isolates obtained from patients diagnosed with gastritis of varying severity (chronic gastritis, antral erosive gastritis, superficial gastritis) in Pereira, Colombia sampled in 2015. Antimicrobial susceptibility tests revealed the isolates to be resistant to at least one of the five antimicrobials tested: four isolates were resistant to metronidazole, two to clarithromycin, two to levofloxacin, and one to rifampin. All isolates were susceptible to tetracycline and amoxicillin. Comparative genome analyses revealed the presence of genes associated with efflux pump, restriction modification systems, phages and insertion sequences, and virulence genes including the cytotoxin genes cagA and vacA. The five genomes represent three novel sequence types. In the context of the Colombian and global populations, the five H. pylori isolates from Pereira were phylogenetically distant to each other but were closely related to other lineages circulating in the country.

CONCLUSIONS

H. pylori from gastritis of different severity varied in their antimicrobial susceptibility profiles and genome content. This knowledge will be useful in implementing appropriate eradication treatment regimens for specific types of gastritis. Understanding the genetic and phenotypic heterogeneity in H. pylori across the geographical landscape is critical in informing health policies for effective disease prevention and management that is most effective at local and country-wide scales. This is especially important in Colombia and other South American countries that are poorly represented in global genomic surveillance studies of bacterial pathogens.

Rapid Whole Genome Characterization of High-Risk Pathogens Using Long-Read Sequencing to Identify Potential Healthcare Transmission

Objective

Routine use of whole genome sequencing (WGS) has been shown to help identify transmission of pathogens causing healthcare-associated infections (HAIs). However, the current gold standard of short-read, Illumina-based WGS is labor and time-intensive. In light of recent improvements in long-read Oxford Nanopore Technologies (ONT) sequencing, we sought to establish a low resource utilization approach capable of providing accurate WGS-based comparisons of HAI pathogens within a time frame allowing for infection prevention and control (IPC) interventions.

Methods

WGS was prospectively performed on antimicrobial-resistant pathogens at increased risk of potential healthcare transmission using the ONT MinION sequencer with R10.4.1 flow cells and Dorado basecalling algorithm. Potential transmission was assessed via Ridom SeqSphere+ for core genome multilocus sequence typing and MINTyper for reference-based core genome single nucleotide polymorphisms using previously published cut-off values. The accuracy of our ONT pipeline was determined relative to Illumina-based WGS data generated from the same genomic DNA sample.

Results

Over a six-month period, 242 bacterial isolates from 216 patients were sequenced by a single operator. Compared to the Illumina gold-standard data, our ONT pipeline achieved a Q score of 60 for assembled genomes, even with a coverage rate of as low as 40X. The mean time from initiating DNA extraction to complete genetic analysis was 2 days (IQR 2-3.25 days). We identified five potential transmission clusters comprising 21 isolates (8.7% of all sequenced strains). Combining ONT WGS data with epidemiological data, >70% (15/21) of the isolates originated from patients with potential healthcare transmission links.

Conclusions

Via a stand-alone ONT pipeline, we detected potentially transmitted HAI pathogens rapidly and accurately, aligning closely with epidemiological data. Our low-resource method has the potential to assist in the efficient detection and deployment of preventative measures against HAI transmission.

Two artificial tears outbreak-associated cases of XDR Pseudomonas aeruginosa detected through whole genome sequencing-based surveillance

We describe two cases of XDR Pseudomonas aeruginosa infection caused by a strain of public health concern recently associated with a nationwide outbreak of contaminated artificial tears. Both cases were detected through database review of genomes in the Enhanced Detection System for Hospital-Associated Transmission (EDS-HAT), a routine genome sequencing-based surveillance program. We generated a high-quality reference genome for the outbreak strain from one of the case isolates from our center and examined the mobile elements encoding bla VIM-80 and bla GES-9 carbapenemases. We then used publicly available P. aeruginosa genomes to explore the genetic relatedness and antimicrobial resistance genes of the outbreak strain.