Mycobacterium ulcerans challenge strain selection for a Buruli ulcer controlled human infection model.

Critical scientific questions remain regarding infection with Mycobacterium ulcerans, the organism responsible for the neglected tropical disease, Buruli ulcer (BU). A controlled human infection model has the potential to accelerate our knowledge of the immunological correlates of disease, to test prophylactic interventions and novel therapeutics. Here we present microbiological evidence supporting M. ulcerans JKD8049 as a suitable human challenge strain. This non-genetically modified Australian isolate is susceptible to clinically relevant antibiotics, can be cultured in animal-free and surfactant-free media, can be enumerated for precise dosing, and has stable viability following cryopreservation. Infectious challenge of humans with JKD8049 is anticipated to imitate natural infection, as M. ulcerans JKD8049 is genetically stable following in vitro passage and produces the key virulence factor, mycolactone. Also reported are considerations for the manufacture, storage, and administration of M. ulcerans JKD8049 for controlled human infection.

High performance Legionella pneumophila source attribution using genomics-based machine learning classification.

Fundamental to effective Legionnaires' disease outbreak control is the ability to rapidly identify the environmental source(s) of the causative agent, Legionella pneumophila. Genomics has revolutionized pathogen surveillance, but L. pneumophila has a complex ecology and population structure that can limit source inference based on standard core genome phylogenetics. Here, we present a powerful machine learning approach that assigns the geographical source of Legionnaires' disease outbreaks more accurately than current core genome comparisons. Models were developed upon 534 L. pneumophila genome sequences, including 149 genomes linked to 20 previously reported Legionnaires' disease outbreaks through detailed case investigations. Our classification models were developed in a cross-validation framework using only environmental L. pneumophila genomes. Assignments of clinical isolate geographic origins demonstrated high predictive sensitivity and specificity of the models, with no false positives or false negatives for 13 out of 20 outbreak groups, despite the presence of within-outbreak polyclonal population structure. Analysis of the same 534-genome panel with a conventional phylogenomic tree and a core genome multi-locus sequence type allelic distance-based classification approach revealed that our machine learning method had the highest overall classification performance-agreement with epidemiological information. Our multivariate statistical learning approach maximizes the use of genomic variation data and is thus well-suited for supporting Legionnaires' disease outbreak investigations.IMPORTANCEIdentifying the sources of Legionnaires' disease outbreaks is crucial for effective control. Current genomic methods, while useful, often fall short due to the complex ecology and population structure of Legionella pneumophila, the causative agent. Our study introduces a high-performing machine learning approach for more accurate geographical source attribution of Legionnaires' disease outbreaks. Developed using cross-validation on environmental L. pneumophila genomes, our models demonstrate excellent predictive sensitivity and specificity. Importantly, this new approach outperforms traditional methods like phylogenomic trees and core genome multi-locus sequence typing, proving more efficient at leveraging genomic variation data to infer outbreak sources. Our machine learning algorithms, harnessing both core and accessory genomic variation, offer significant promise in public health settings. By enabling rapid and precise source identification in Legionnaires' disease outbreaks, such approaches have the potential to expedite intervention efforts and curtail disease transmission.

Mosquitoes provide a transmission route between possums and humans for Buruli ulcer in southeastern Australia.

Buruli ulcer, a chronic subcutaneous infection caused by Mycobacterium ulcerans, is increasing in prevalence in southeastern Australia. Possums are a local wildlife reservoir for M. ulcerans and, although mosquitoes have been implicated in transmission, it remains unclear how humans acquire infection. We conducted extensive field survey analyses of M. ulcerans prevalence among mosquitoes in the Mornington Peninsula region of southeastern Australia. PCR screening of trapped mosquitoes revealed a significant association between M. ulcerans and Aedes notoscriptus. Spatial scanning statistics revealed overlap between clusters of M. ulcerans-positive Ae. notoscriptus, M. ulcerans-positive possum excreta and Buruli ulcer cases, and metabarcoding analyses showed individual mosquitoes had fed on humans and possums. Bacterial genomic analysis confirmed shared single-nucleotide-polymorphism profiles for M. ulcerans detected in mosquitoes, possum excreta and humans. These findings indicate Ae. notoscriptus probably transmit M. ulcerans in southeastern Australia and highlight mosquito control as a Buruli ulcer prevention measure.

Statistical modeling based on structured surveys of Australian native possum excreta harboring Mycobacterium ulcerans predicts Buruli ulcer occurrence in humans.

Background: Buruli ulcer (BU) is a neglected tropical disease caused by infection of subcutaneous tissue with Mycobacterium ulcerans. BU is commonly reported across rural regions of Central and West Africa but has been increasing dramatically in temperate southeast Australia around the major metropolitan city of Melbourne, with most disease transmission occurring in the summer months. Previous research has shown that Australian native possums are reservoirs of M. ulcerans and that they shed the bacteria in their fecal material (excreta). Field surveys show that locales where possums harbor M. ulcerans overlap with human cases of BU, raising the possibility of using possum excreta surveys to predict the risk of disease occurrence in humans. Methods: We thus established a highly structured 12 month possum excreta surveillance program across an area of 350 km2 in the Mornington Peninsula area 70 km south of Melbourne, Australia. The primary objective of our study was to assess using statistical modeling if M. ulcerans surveillance of possum excreta provided useful information for predicting future human BU case locations. Results: Over two sampling campaigns in summer and winter, we collected 2,282 possum excreta specimens of which 11% were PCR positive for M. ulcerans-specific DNA. Using the spatial scanning statistical tool SaTScan, we observed non-random, co-correlated clustering of both M. ulcerans positive possum excreta and human BU cases. We next trained a statistical model with the Mornington Peninsula excreta survey data to predict the future likelihood of human BU cases occurring in the region. By observing where human BU cases subsequently occurred, we show that the excreta model performance was superior to a null model trained using the previous year's human BU case incidence data (AUC 0.66 vs 0.55). We then used data unseen by the excreta-informed model from a new survey of 661 possum excreta specimens in Geelong, a geographically separate BU endemic area to the southwest of Melbourne, to prospectively predict the location of human BU cases in that region. As for the Mornington Peninsula, the excreta-based BU prediction model outperformed the null model (AUC 0.75 vs 0.50) and pinpointed specific locations in Geelong where interventions could be deployed to interrupt disease spread. Conclusions: This study highlights the One Health nature of BU by confirming a quantitative relationship between possum excreta shedding of M. ulcerans and humans developing BU. The excreta survey-informed modeling we have described will be a powerful tool for the efficient targeting of public health responses to stop BU. Funding: This research was supported by the National Health and Medical Research Council of Australia and the Victorian Government Department of Health (GNT1152807 and GNT1196396).

Low-Cost, Open-Source Device for High-Performance Fluorescence Detection of Isothermal Nucleic Acid Amplification Reactions.

The ability to detect SARS-CoV-2 is critical to implementing evidence-based strategies to address the COVID-19 global pandemic. Expanding SARS-CoV-2 diagnostic ability beyond well-equipped laboratories widens the opportunity for surveillance and control efforts. However, such advances are predicated on the availability of rapid, scalable, accessible, yet high-performance diagnostic platforms. Methods to detect viral RNA using reverse transcription loop-mediated isothermal amplification (RT-LAMP) show promise as rapid and field-deployable tests; however, the per-unit costs of the required diagnostic hardware can be a barrier for scaled deployment. Here, we describe a diagnostic hardware configuration for LAMP technology, named the FABL-8, that can be built for approximately US$380 per machine and provide results in under 30 min. Benchmarking showed that FABL-8 has a similar performance to a high-end commercial instrument for detecting fluorescence-based LAMP reactions. Performance testing of the instrument with RNA extracted from a SARS-CoV-2 virus dilution series revealed an analytical detection sensitivity of 50 virus copies per microliter-a detection threshold suitable to detect patient viral load in the first few days following symptom onset. In addition to the detection of SARS-CoV-2, we show that the system can be used to detect the presence of two bacterial pathogens, demonstrating the versatility of the platform for the detection of other pathogens. This cost-effective and scalable hardware alternative allows democratization of the instrumentation required for high-performance molecular diagnostics, such that it could be available to laboratories anywhere-supporting infectious diseases surveillance and research activities in resource-limited settings.

Accessible Platform for High-Throughput COVID-19 Molecular Diagnostics and Genome Sequencing Using a Repurposed 3D Printer for RNA Extraction.

The COVID-19 pandemic has exposed the dependence of diagnostic laboratories on a handful of large corporations with market monopolies on the worldwide supply of reagents, consumables, and hardware for molecular diagnostics. Global shortages of key consumables for RT-qPCR detection of SARS-CoV-2 RNA have impaired the ability to run essential, routine diagnostic services. Here, we describe a workflow for rapid detection of SARS-CoV-2 RNA in upper respiratory samples including nasal swabs and saliva, utilizing low-cost equipment and readily accessible reagents. Using repurposed Creality3D Ender-3 three-dimensional (3D) printers, we built a semiautomated paramagnetic bead RNA extraction platform. The hardware for the system was built for $300 USD, and the material cost per reaction was $1 USD. Named the Ender VX500, instrument performance when paired with RT-qPCR for SARS-CoV-2 detection in nasal and saliva specimens was two virus copies per microliter. There was a high-performance agreement (assessed using 458 COVID-19 nasal swab specimens) with the Aptima SARS-CoV-2 assay run on the Hologic Panther, a commercial automated RNA extraction and detection platform. Inter- and intrainstrument precision was excellent (coefficients of variation (CoV) of 1.10 and 0.66-1.32%, respectively) across four instruments. The platform is scalable with throughput ranging from 23 specimens on a single instrument run by one user in 50 min to 364 specimens on four instruments run by four users in 190 min. Step-by-step instructions and protocols for building and running the Ender VX500 have been made available without restriction.

Vaccine-Specific Immune Responses against Mycobacterium ulcerans Infection in a Low-Dose Murine Challenge Model.

The neglected tropical disease Buruli ulcer (BU) is an infection of subcutaneous tissue with Mycobacterium ulcerans There is no effective vaccine. Here, we assessed an experimental prime-boost vaccine in a low-dose murine tail infection model. We used the enoyl reductase (ER) domain of the M. ulcerans mycolactone polyketide synthases electrostatically coupled with a previously described Toll-like receptor 2 (TLR-2) agonist-based lipopeptide adjuvant, R4Pam2Cys. Mice were vaccinated and then challenged via tail inoculation with 14 to 20 CFU of a bioluminescent strain of M. ulcerans Mice receiving either the experimental ER vaccine or Mycobacterium bovis bacillus Calmette-Guérin (BCG) were equally protected, with both groups faring significantly better than nonvaccinated animals (P < 0.05). To explore potential correlates of protection, a suite of 29 immune parameters were assessed in the mice at the end of the experimental period. Multivariate statistical approaches were used to interrogate the immune response data to develop disease-prognostic models. High levels of interleukin 2 (IL-2) and low gamma interferon (IFN-γ) produced in the spleen best predicted control of infection across all vaccine groups. Univariate logistic regression revealed vaccine-specific profiles of protection. High titers of ER-specific IgG serum antibodies together with IL-2 and IL-4 in the draining lymph node (DLN) were associated with protection induced by the ER vaccine. In contrast, high titers of IL-6, tumor necrosis factor alpha (TNF-α), IFN-γ, and IL-10 in the DLN and low IFN-γ titers in the spleen were associated with protection following BCG vaccination. This study suggests that an effective BU vaccine must induce localized, tissue-specific immune profiles with controlled inflammatory responses at the site of infection.

Buruli ulcers in a Spanish aid worker after a stay in Peru.

Buruli ulcer (BU) is a chronic and destructive infection of the skin and soft tissues caused by Mycobacterium ulcerans. Recently, population flows have triggered the appearance of several sporadic cases of BU in non-endemic countries. This represents a significant diagnostic challenge for clinicians and microbiologists. We describe the first case of BU imported to Spain. The patient was a Spanish woman who had stayed 5 months in the jungle of Peru.

Increasing tolerance of hospital Enterococcus faecium to handwash alcohols.

Alcohol-based disinfectants and particularly hand rubs are a key way to control hospital infections worldwide. Such disinfectants restrict transmission of pathogens, such as multidrug-resistant Staphylococcus aureus and Enterococcus faecium Despite this success, health care infections caused by E. faecium are increasing. We tested alcohol tolerance of 139 hospital isolates of E. faecium obtained between 1997 and 2015 and found that E. faecium isolates after 2010 were 10-fold more tolerant to killing by alcohol than were older isolates. Using a mouse gut colonization model of E. faecium transmission, we showed that alcohol-tolerant E. faecium resisted standard 70% isopropanol surface disinfection, resulting in greater mouse gut colonization compared to alcohol-sensitive E. faecium We next looked for bacterial genomic signatures of adaptation. Alcohol-tolerant E. faecium accumulated mutations in genes involved in carbohydrate uptake and metabolism. Mutagenesis confirmed the roles of these genes in the tolerance of E. faecium to isopropanol. These findings suggest that bacterial adaptation is complicating infection control recommendations, necessitating additional procedures to prevent E. faecium from spreading in hospital settings.

Vancomycin-resistant Enterococcus faecium sequence type 796 - rapid international dissemination of a new epidemic clone.

Background: Vancomycin-resistant Enterococcus faecium (VRE) is a leading cause of hospital-acquired infections. New, presumably better-adapted strains of VRE appear unpredictably; it is uncertain how they spread despite improved infection control. We aimed to investigate the relatedness of a novel sequence type (ST) of vanB E. faecium - ST796 - very near its time of origin from hospitals in three Australian states and New Zealand. Methods: Following near-simultaneous outbreaks of ST796 in multiple institutions, we gathered then tested colonization and bloodstream infection isolates' antimicrobial resistance (AMR) phenotypes, and phylogenomic relationships using whole genome sequencing (WGS). Patient meta-data was explored to trace the spread of ST796. Results: A novel clone of vanB E. faecium (ST796) was first detected at one Australian hospital in late 2011, then in two New Zealand hospitals linked by inter-hospital transfers from separate Melbourne hospitals. ST796 also appeared in hospitals in South Australia and New South Wales and was responsible for at least one major colonization outbreak in a Neonatal Intensive Care Unit without identifiable links between centers. No exceptional AMR was detected in the isolates. While WGS analysis showed very limited diversity at the core genome, consistent with recent emergence of the clone, clustering by institution was observed. Conclusions: Evolution of new E. faecium clones, followed by recognized or unrecognized movement of colonized individuals then rapid intra-institutional cross-transmission best explain the multi-center, multistate and international outbreak we observed.

Comparative Genomics Shows That Mycobacterium ulcerans Migration and Expansion Preceded the Rise of Buruli Ulcer in Southeastern Australia.

Since 2000, cases of the neglected tropical disease Buruli ulcer, caused by infection with Mycobacterium ulcerans, have increased 100-fold around Melbourne (population 4.4 million), the capital of Victoria, in temperate southeastern Australia. The reasons for this increase are unclear. Here, we used whole-genome sequence comparisons of 178 M. ulcerans isolates obtained primarily from human clinical specimens, spanning 70 years, to model the population dynamics of this pathogen from this region. Using phylogeographic and advanced Bayesian phylogenetic approaches, we found that there has been a migration of the pathogen from the east end of the state, beginning in the 1980s, 300 km west to the major human population center around Melbourne. This move was then followed by a significant increase in M. ulcerans population size. These analyses inform our thinking around Buruli ulcer transmission and control, indicating that M. ulcerans is introduced to a new environment and then expands, rather than it being from the awakening of a quiescent pathogen reservoir.IMPORTANCE Buruli ulcer is a destructive skin and soft tissue infection caused by Mycobacterium ulcerans and is characterized by progressive skin ulceration, which can lead to permanent disfigurement and long-term disability. Despite the majority of disease burden occurring in regions of West and central Africa, Buruli ulcer is also becoming increasingly common in southeastern Australia. Major impediments to controlling disease spread are incomplete understandings of the environmental reservoirs and modes of transmission of M. ulcerans The significance of our research is that we used genomics to assess the population structure of this pathogen at the Australian continental scale. We have then reconstructed a historical bacterial spread and modeled demographic dynamics to reveal bacterial population expansion across southeastern Australia. These findings provide explanations for the observed epidemiological trends with Buruli ulcer and suggest possible management to control disease spread.

Methicillin Resistant Staphylococcus aureus Transmission in a Ghanaian Burn Unit: The Importance of Active Surveillance in Resource-Limited Settings.

Objectives:Staphylococcus aureus infections in burn patients can lead to serious complications and death. The frequency of S. aureus infection is high in low- and middle-income countries presumably due to limited resources, misuse of antibiotics and poor infection control. The objective of the present study was to apply population genomics to precisely define, for the first time, the transmission of antibiotic resistant S. aureus in a resource-limited setting in sub-Saharan Africa. Methods:Staphylococcus aureus surveillance was performed amongst burn patients and healthcare workers during a 7-months survey within the burn unit of the Korle Bu Teaching Hospital in Ghana. Results: Sixty-six S. aureus isolates (59 colonizing and 7 clinical) were obtained from 31 patients and 10 healthcare workers. Twenty-one of these isolates were ST250-IV methicillin-resistant S. aureus (MRSA). Notably, 25 (81%) of the 31 patients carried or were infected with S. aureus within 24 h of admission. Genome comparisons revealed six distinct S. aureus clones circulating in the burn unit, and demonstrated multiple transmission events between patients and healthcare workers. Further, the collected S. aureus isolates exhibited a wide range of genotypic resistances to antibiotics, including trimethoprim (21%), aminoglycosides (33%), oxacillin (33%), chloramphenicol (50%), tetracycline (59%) and fluoroquinolones (100%). Conclusion: Population genomics uncovered multiple transmission events of S. aureus, especially MRSA, within the investigated burn unit. Our findings highlight lapses in infection control and prevention, and underscore the great importance of active surveillance to protect burn victims against multi-drug resistant pathogens in resource-limited settings.

A Supervised Statistical Learning Approach for Accurate Legionella pneumophila Source Attribution during Outbreaks.

Public health agencies are increasingly relying on genomics during Legionnaires' disease investigations. However, the causative bacterium (Legionella pneumophila) has an unusual population structure, with extreme temporal and spatial genome sequence conservation. Furthermore, Legionnaires' disease outbreaks can be caused by multiple L. pneumophila genotypes in a single source. These factors can confound cluster identification using standard phylogenomic methods. Here, we show that a statistical learning approach based on L. pneumophila core genome single nucleotide polymorphism (SNP) comparisons eliminates ambiguity for defining outbreak clusters and accurately predicts exposure sources for clinical cases. We illustrate the performance of our method by genome comparisons of 234 L. pneumophila isolates obtained from patients and cooling towers in Melbourne, Australia, between 1994 and 2014. This collection included one of the largest reported Legionnaires' disease outbreaks, which involved 125 cases at an aquarium. Using only sequence data from L. pneumophila cooling tower isolates and including all core genome variation, we built a multivariate model using discriminant analysis of principal components (DAPC) to find cooling tower-specific genomic signatures and then used it to predict the origin of clinical isolates. Model assignments were 93% congruent with epidemiological data, including the aquarium Legionnaires' disease outbreak and three other unrelated outbreak investigations. We applied the same approach to a recently described investigation of Legionnaires' disease within a UK hospital and observed a model predictive ability of 86%. We have developed a promising means to breach L. pneumophila genetic diversity extremes and provide objective source attribution data for outbreak investigations.IMPORTANCE Microbial outbreak investigations are moving to a paradigm where whole-genome sequencing and phylogenetic trees are used to support epidemiological investigations. It is critical that outbreak source predictions are accurate, particularly for pathogens, like Legionella pneumophila, which can spread widely and rapidly via cooling system aerosols, causing Legionnaires' disease. Here, by studying hundreds of Legionella pneumophila genomes collected over 21 years around a major Australian city, we uncovered limitations with the phylogenetic approach that could lead to a misidentification of outbreak sources. We implement instead a statistical learning technique that eliminates the ambiguity of inferring disease transmission from phylogenies. Our approach takes geolocation information and core genome variation from environmental L. pneumophila isolates to build statistical models that predict with high confidence the environmental source of clinical L. pneumophila during disease outbreaks. We show the versatility of the technique by applying it to unrelated Legionnaires' disease outbreaks in Australia and the UK.

Exposure Risk for Infection and Lack of Human-to-Human Transmission of Mycobacterium ulcerans Disease, Australia.

We conducted epidemiologic and genetic analyses of family clusters of Mycobacterium ulcerans (Buruli ulcer) disease in southeastern Australia. We found that the incidence of M. ulcerans disease in family members was increased. However, the risk for exposure appeared short-term and not related to human-human transmission.

Genomic analysis of ST88 community-acquired methicillin resistant Staphylococcus aureus in Ghana.

BACKGROUND: The emergence and evolution of community-acquired methicillin resistant Staphylococcus aureus (CA-MRSA) strains in Africa is poorly understood. However, one particular MRSA lineage called ST88, appears to be rapidly establishing itself as an "African" CA-MRSA clone. In this study, we employed whole genome sequencing to provide more information on the genetic background of ST88 CA-MRSA isolates from Ghana and to describe in detail ST88 CA-MRSA isolates in comparison with other MRSA lineages worldwide. METHODS: We first established a complete ST88 reference genome (AUS0325) using PacBio SMRT sequencing. We then used comparative genomics to assess relatedness among 17 ST88 CA-MRSA isolates recovered from patients attending Buruli ulcer treatment centres in Ghana, three non-African ST88s and 15 other MRSA lineages. RESULTS: We show that Ghanaian ST88 forms a discrete MRSA lineage (harbouring SCCmec-IV [2B]). Gene content analysis identified five distinct genomic regions enriched among ST88 isolates compared with the other S. aureus lineages. The Ghanaian ST88 isolates had only 658 core genome SNPs and there was no correlation between phylogeny and geography, suggesting the recent spread of this clone. The lineage was also resistant to multiple classes of antibiotics including ß-lactams, tetracycline and chloramphenicol. DISCUSSION: This study reveals that S. aureus ST88-IV is a recently emerging and rapidly spreading CA-MRSA clone in Ghana. The study highlights the capacity of small snapshot genomic studies to provide actionable public health information in resource limited settings. To our knowledge this is the first genomic assessment of the ST88 CA-MRSA clone.

Evolutionary origins of the emergent ST796 clone of vancomycin resistant Enterococcus faecium.

From early 2012, a novel clone of vancomycin resistant Enterococcus faecium (assigned the multi locus sequence type ST796) was simultaneously isolated from geographically separate hospitals in south eastern Australia and New Zealand. Here we describe the complete genome sequence of Ef_aus0233, a representative ST796 E. faecium isolate. We used PacBio single molecule real-time sequencing to establish a high quality, fully assembled genome comprising a circular chromosome of 2,888,087 bp and five plasmids. Comparison of Ef_aus0233 to other E. faecium genomes shows Ef_aus0233 is a member of the epidemic hospital-adapted lineage and has evolved from an ST555-like ancestral progenitor by the accumulation or modification of five mosaic plasmids and five putative prophage, acquisition of two cryptic genomic islands, accrued chromosomal single nucleotide polymorphisms and a 80 kb region of recombination, also gaining Tn1549 and Tn916, transposons conferring resistance to vancomycin and tetracycline respectively. The genomic dissection of this new clone presented here underscores the propensity of the hospital E. faecium lineage to change, presumably in response to the specific conditions of hospital and healthcare environments.

Emergence of endemic MLST non-typeable vancomycin-resistant Enterococcus faecium.

BACKGROUND: Enterococcus faecium is a major nosocomial pathogen causing significant morbidity and mortality worldwide. Assessment of E. faecium using MLST to understand the spread of this organism is an important component of hospital infection control measures. Recent studies, however, suggest that MLST might be inadequate for E. faecium surveillance. OBJECTIVES: To use WGS to characterize recently identified vancomycin-resistant E. faecium (VREfm) isolates non-typeable by MLST that appear to be causing a multi-jurisdictional outbreak in Australia. METHODS: Illumina NextSeq and Pacific Biosciences SMRT sequencing platforms were used to determine the genome sequences of 66 non-typeable E. faecium (NTEfm) isolates. Phylogenetic and bioinformatics analyses were subsequently performed using a number of in silico tools. RESULTS: Sixty-six E. faecium isolates were identified by WGS from multiple health jurisdictions in Australia that could not be typed by MLST due to a missing pstS allele. SMRT sequencing and complete genome assembly revealed a large chromosomal rearrangement in representative strain DMG1500801, which likely facilitated the deletion of the pstS region. Phylogenomic analysis of this population suggests that deletion of pstS within E. faecium has arisen independently on at least three occasions. Importantly, the majority of these isolates displayed a vancomycin-resistant genotype. CONCLUSIONS: We have identified NTEfm isolates that appear to be causing a multi-jurisdictional outbreak in Australia. Identification of these isolates has important implications for MLST-based typing activities designed to monitor the spread of VREfm and provides further evidence supporting the use of WGS for hospital surveillance of E. faecium.