Evaluating the impact of genomic epidemiology of methicillin-resistant Staphylococcus aureus (MRSA) on hospital infection prevention and control decisions.

Genomic epidemiology enhances the ability to detect and refute methicillin-resistant Staphylococcus aureus (MRSA) outbreaks in healthcare settings, but its routine introduction requires further evidence of benefits for patients and resource utilization. We performed a 12 month prospective study at Cambridge University Hospitals NHS Foundation Trust in the UK to capture its impact on hospital infection prevention and control (IPC) decisions. MRSA-positive samples were identified via the hospital microbiology laboratory between November 2018 and November 2019. We included samples from in-patients, clinic out-patients, people reviewed in the Emergency Department and healthcare workers screened by Occupational Health. We sequenced the first MRSA isolate from 823 consecutive individuals, defined their pairwise genetic relatedness, and sought epidemiological links in the hospital and community. Genomic analysis of 823 MRSA isolates identified 72 genetic clusters of two or more isolates containing 339/823 (41 %) of the cases. Epidemiological links were identified between two or more cases for 190 (23 %) individuals in 34/72 clusters. Weekly genomic epidemiology updates were shared with the IPC team, culminating in 49 face-to-face meetings and 21 written communications. Seventeen clusters were identified that were consistent with hospital MRSA transmission, discussion of which led to additional IPC actions in 14 of these. Two outbreaks were also identified where transmission had occurred in the community prior to hospital presentation; these were escalated to relevant IPC teams. We identified 38 instances where two or more in-patients shared a ward location on overlapping dates but carried unrelated MRSA isolates (pseudo-outbreaks); research data led to de-escalation of investigations in six of these. Our findings provide further support for the routine use of genomic epidemiology to enhance and target IPC resources.

Antibiotic resistance determination using Enterococcus faecium whole-genome sequences: a diagnostic accuracy study using genotypic and phenotypic data.

BACKGROUND: DNA sequencing could become an alternative to in vitro antibiotic susceptibility testing (AST) methods for determining antibiotic resistance by detecting genetic determinants associated with decreased antibiotic susceptibility. Here, we aimed to assess and improve the accuracy of antibiotic resistance determination from Enterococcus faecium genomes for diagnosis and surveillance purposes. METHODS: In this retrospective diagnostic accuracy study, we first conducted a literature search in PubMed on Jan 14, 2021, to compile a catalogue of genes and mutations predictive of antibiotic resistance in E faecium. We then evaluated the diagnostic accuracy of this database to determine susceptibility to 12 different, clinically relevant antibiotics using a diverse population of 4382 E faecium isolates with available whole-genome sequences and in vitro culture-based AST phenotypes. Isolates were obtained from various sources in 11 countries worldwide between 2000 and 2018. We included isolates tested with broth microdilution, Vitek 2, and disc diffusion, and antibiotics with at least 50 susceptible and 50 resistant isolates. Phenotypic resistance was derived from raw minimum inhibitory concentrations and measured inhibition diameters, and harmonised primarily using the breakpoints set by the European Committee on Antimicrobial Susceptibility Testing. A bioinformatics pipeline was developed to process raw sequencing reads, identify antibiotic resistance genetic determinants, and report genotypic resistance. We used our curated database, as well as ResFinder, AMRFinderPlus, and LRE-Finder, to assess the accuracy of genotypic predictions against phenotypic resistance. FINDINGS: We curated a catalogue of 228 genetic markers involved in resistance to 12 antibiotics in E faecium. Very accurate genotypic predictions were obtained for ampicillin (sensitivity 99·7% [95% CI 99·5-99·9] and specificity 97·9% [95·8-99·0]), ciprofloxacin (98·0% [96·4-98·9] and 98·8% [95·9-99·7]), vancomycin (98·8% [98·3-99·2] and 98·8% [98·0-99·3]), and linezolid resistance (after re-testing false negatives: 100·0% [90·8-100·0] and 98·3% [97·8-98·7]). High sensitivity was obtained for tetracycline (99·5% [99·1-99·7]), teicoplanin (98·9% [98·4-99·3]), and high-level resistance to aminoglycosides (97·7% [96·6-98·4] for streptomycin and 96·8% [95·8-97·5] for gentamicin), although at lower specificity (60-90%). Sensitivity was expectedly low for daptomycin (73·6% [65·1-80·6]) and tigecycline (38·3% [27·1-51·0]), for which the genetic basis of resistance is not fully characterised. Compared with other antibiotic resistance databases and bioinformatic tools, our curated database was similarly accurate at detecting resistance to ciprofloxacin and linezolid and high-level resistance to streptomycin and gentamicin, but had better sensitivity for detecting resistance to ampicillin, tigecycline, daptomycin, and quinupristin-dalfopristin, and better specificity for ampicillin, vancomycin, teicoplanin, and tetracycline resistance. In a validation dataset of 382 isolates, similar or improved diagnostic accuracies were also achieved. INTERPRETATION: To our knowledge, this work represents the largest published evaluation to date of the accuracy of antibiotic susceptibility predictions from E faecium genomes. The results and resources will facilitate the adoption of whole-genome sequencing as a tool for the diagnosis and surveillance of antimicrobial resistance in E faecium. A complete characterisation of the genetic basis of resistance to last-line antibiotics, and the mechanisms mediating antibiotic resistance silencing, are needed to close the remaining sensitivity and specificity gaps in genotypic predictions. FUNDING: Wellcome Trust, UK Department of Health, British Society for Antimicrobial Chemotherapy, Academy of Medical Sciences and the Health Foundation, Medical Research Council Newton Fund, Vietnamese Ministry of Science and Technology, and European Society of Clinical Microbiology and Infectious Disease.

Large-Scale Evaluation of a Rapid Fully Automated Analysis Platform to Detect and Refute Outbreaks Based on MRSA Genome Comparisons.

Genomic epidemiology of methicillin-resistant Staphylococcus aureus (MRSA) could transform outbreak investigations, but its clinical introduction is hampered by the lack of automated data analysis tools to rapidly and accurately define transmission based on sequence relatedness. We aimed to evaluate a fully automated bioinformatics system for MRSA genome analysis versus a bespoke researcher-led manual informatics pipeline. We analyzed 781 MRSA genomes from 777 consecutive patients identified over a 9-month period in a clinical microbiology laboratory in the United Kingdom. Outputs were bacterial species identification, detection of mec genes, assignment to sequence types (STs), identification of pairwise relatedness using a definition of ≤25 single nucleotide polymorphisms (SNPs) apart, and use of genetic relatedness to identify clusters. There was full concordance between the two analysis methods for species identification, detection of mec genes, and ST assignment. A total of 3,311 isolate pairs ≤25 SNPs apart were identified by at least one method. These had a median (range) SNP difference between the two methods of 1.2 SNPs (0 to 22 SNPs), with most isolate pairs (87%) varying by ≤2 SNPs. This similarity increased when the research pipeline was modified to use a clonal-complex-specific reference (median 0 SNP difference, 91% varying by ≤2 SNPs). Both pipelines clustered 338 isolates/334 patients into 66 unique clusters based on genetic relatedness. We conclude that the automated transmission detection tool worked at least as well as a researcher-led manual analysis and indicates how such tools could support the rapid use of MRSA genomic epidemiology in infection control practice. IMPORTANCE It has been clearly established that genome sequencing of MRSA improves the accuracy of health care-associated outbreak investigations, including the confirmation and exclusion of outbreaks and identification of patients involved. This could lead to more targeted infection control actions but its use in clinical practice is prevented by several barriers, one of which is the availability of genome analysis tools that do not depend on specialist knowledge to analyze or interpret the results. We evaluated a prototype of a fully automated bioinformatics system for MRSA genome analysis versus a bespoke researcher-led manual informatics pipeline, using genomes from 777 patients over a period of 9 months. The performance was at least equivalent to the researcher-led manual genomic analysis. This indicates the feasibility of automated analysis and represents one more step toward the routine use of pathogen sequencing in infection prevention and control practice.

Exploring the mobilome and resistome of Enterococcus faecium in a One Health context across two continents.

Enterococcus faecium is a ubiquitous opportunistic pathogen that is exhibiting increasing levels of antimicrobial resistance (AMR). Many of the genes that confer resistance and pathogenic functions are localized on mobile genetic elements (MGEs), which facilitate their transfer between lineages. Here, features including resistance determinants, virulence factors and MGEs were profiled in a set of 1273 E. faecium genomes from two disparate geographic locations (in the UK and Canada) from a range of agricultural, clinical and associated habitats. Neither lineages of E. faecium, type A and B, nor MGEs are constrained by geographic proximity, but our results show evidence of a strong association of many profiled genes and MGEs with habitat. Many features were associated with a group of clinical and municipal wastewater genomes that are likely forming a new human-associated ecotype within type A. The evolutionary dynamics of E. faecium make it a highly versatile emerging pathogen, and its ability to acquire, transmit and lose features presents a high risk for the emergence of new pathogenic variants and novel resistance combinations. This study provides a workflow for MGE-centric surveillance of AMR in Enterococcus that can be adapted to other pathogens.

PowerBacGWAS: a computational pipeline to perform power calculations for bacterial genome-wide association studies.

Genome-wide association studies (GWAS) are increasingly being applied to investigate the genetic basis of bacterial traits. However, approaches to perform power calculations for bacterial GWAS are limited. Here we implemented two alternative approaches to conduct power calculations using existing collections of bacterial genomes. First, a sub-sampling approach was undertaken to reduce the allele frequency and effect size of a known and detectable genotype-phenotype relationship by modifying phenotype labels. Second, a phenotype-simulation approach was conducted to simulate phenotypes from existing genetic variants. We implemented both approaches into a computational pipeline (PowerBacGWAS) that supports power calculations for burden testing, pan-genome and variant GWAS; and applied it to collections of Enterococcus faecium, Klebsiella pneumoniae and Mycobacterium tuberculosis. We used this pipeline to determine sample sizes required to detect causal variants of different minor allele frequencies (MAF), effect sizes and phenotype heritability, and studied the effect of homoplasy and population diversity on the power to detect causal variants. Our pipeline and user documentation are made available and can be applied to other bacterial populations. PowerBacGWAS can be used to determine sample sizes required to find statistically significant associations, or the associations detectable with a given sample size. We recommend to perform power calculations using existing genomes of the bacterial species and population of study.

A common protocol for the simultaneous processing of multiple clinically relevant bacterial species for whole genome sequencing.

Whole-genome sequencing is likely to become increasingly used by local clinical microbiology laboratories, where sequencing volume is low compared with national reference laboratories. Here, we describe a universal protocol for simultaneous DNA extraction and sequencing of numerous different bacterial species, allowing mixed species sequence runs to meet variable laboratory demand. We assembled test panels representing 20 clinically relevant bacterial species. The DNA extraction process used the QIAamp mini DNA kit, to which different combinations of reagents were added. Thereafter, a common protocol was used for library preparation and sequencing. The addition of lysostaphin, lysozyme or buffer ATL (a tissue lysis buffer) alone did not produce sufficient DNA for library preparation across the species tested. By contrast, lysozyme plus lysostaphin produced sufficient DNA across all 20 species. DNA from 15 of 20 species could be extracted from a 24-h culture plate, while the remainder required 48-72 h. The process demonstrated 100% reproducibility. Sequencing of the resulting DNA was used to recapitulate previous findings for species, outbreak detection, antimicrobial resistance gene detection and capsular type. This single protocol for simultaneous processing and sequencing of multiple bacterial species supports low volume and rapid turnaround time by local clinical microbiology laboratories.

Quantifying acquisition and transmission of Enterococcus faecium using genomic surveillance.

Nosocomial acquisition and transmission of vancomycin-resistant Enterococcus faecium (VREfm) is the driver for E. faecium carriage in hospitalized patients, which, in turn, is a risk factor for invasive infection in immunocompromised patients. In the present study, we provide a comprehensive picture of E. faecium transmission in an entire sampled patient population using a sequence-driven approach. We prospectively identified and followed 149 haematology patients admitted to a hospital in England for 6 months. Patient stools (n = 376) and environmental swabs (n = 922) were taken at intervals and cultured for E. faecium. We sequenced 1,560 isolates (1,001 stool, 559 environment) and focused our genomic analyses on 1,477 isolates (95%) in the hospital-adapted clade A1. Of 101 patients who provided two or more stool samples, 40 (40%) developed E. faecium carriage after admission based on culture, compared with 64 patients (63%) based on genomic analysis (73% VREfm). Half of 922 environmental swabs (447, 48%) were positive for VREfm. Network analysis showed that, of 111 patients positive for the A1 clade, 67 had strong epidemiological and genomic links with at least one other patient and/or their direct environment, supporting nosocomial transmission. Six patients (3.4%) developed an invasive E. faecium infection from their own gut-colonizing strain, which was preceded by nosocomial acquisition of the infecting isolate in half of these. Two informatics approaches (subtype categorization to define phylogenetic clusters and the development of an SNP cut-off for transmission) were central to our analyses, both of which will inform the future translation of E. faecium sequencing into routine outbreak detection and investigation. In conclusion, we showed that carriage and environmental contamination by the hospital-adapted E. faecium lineage were hyperendemic in our study population and that improved infection control measures will be needed to reduce hospital acquisition rates.

Definition of a genetic relatedness cutoff to exclude recent transmission of meticillin-resistant Staphylococcus aureus: a genomic epidemiology analysis.

BACKGROUND: Whole-genome sequencing (WGS) can be used in genomic epidemiology investigations to confirm or refute outbreaks of bacterial pathogens, and to support targeted and efficient infection control interventions. We aimed to define a genetic relatedness cutoff, quantified as a number of single-nucleotide polymorphisms (SNP), for meticillin-resistant Staphylococcus aureus (MRSA), above which recent (ie, within 6 months) patient-to-patient transmission could be ruled out. METHODS: We did a retrospective genomic and epidemiological analysis of MRSA data from two prospective observational cohort studies in the UK to establish SNP cutoffs for genetic relatedness, above which recent transmission was unlikely. We used three separate approaches to calculate these thresholds. First, we applied a linear mixed model to estimate the S aureus substitution rate and 95th percentile within-host diversity in a cohort in which multiple isolates were sequenced per individual. Second, we applied a simulated transmission model to this same genomic dataset. Finally, in a second cohort, we determined the genetic distance (ie, the number of SNPs) that would capture 95% of epidemiologically linked cases. We applied the three approaches to both whole-genome and core-genome sequences. FINDINGS: In the linear mixed model, the estimated substitution rate was roughly 5 whole-genome SNPs (wgSNPs) or 3 core-genome SNPs (cgSNPs) per genome per year, and the 95th percentile within-host diversity was 19 wgSNPs or 10 cgSNPs. The combined SNP cutoffs for detection of MRSA transmission within 6 months per this model were thus 24 wgSNPs or 13 cgSNPs. The simulated transmission model suggested that cutoffs of 17 wgSNPs or 12 cgSNPs would detect 95% of MRSA transmission events within the same timeframe. Finally, in the second cohort, cutoffs of 22 wgSNPs or 11 cgSNPs captured 95% of epidemiologically linked cases within 6 months. INTERPRETATION: On the basis of our results, we propose conservative cutoffs of 25 wgSNPs or 15 cgSNPS above which transmission of MRSA within the previous 6 months can be ruled out. These cutoffs could potentially be used as part of a genomic sequencing approach to the management of outbreaks of MRSA in conjunction with traditional epidemiological techniques. FUNDING: UK Department of Health, Wellcome Trust, UK National Institute for Health Research.

Defining metrics for whole-genome sequence analysis of MRSA in clinical practice.

Bacterial sequencing will become increasingly adopted in routine microbiology laboratories. Here, we report the findings of a technical evaluation of almost 800 clinical methicillin-resistant Staphylococcus aureus (MRSA) isolates, in which we sought to define key quality metrics to support MRSA sequencing in clinical practice. We evaluated the accuracy of mapping to a generic reference versus clonal complex (CC)-specific mapping, which is more computationally challenging. Focusing on isolates that were genetically related (<50 single nucleotide polymorphisms (SNPs)) and belonged to prevalent sequence types, concordance between these methods was 99.5 %. We use MRSA MPROS0386 to control for base calling accuracy by the sequencer, and used multiple repeat sequences of the control to define a permitted range of SNPs different to the mapping reference for this control (equating to 3 standard deviations from the mean). Repeat sequences of the control were also used to demonstrate that SNP calling was most accurate across differing coverage depths (above 35×, the lowest depth in our study) when the depth required to call a SNP as present was at least 4-8×. Using 786 MRSA sequences, we defined a robust measure for mec gene detection to reduce false-positives arising from contamination, which was no greater than 2 standard deviations below the average depth of coverage across the genome. Sequencing from bacteria harvested from clinical plates runs an increased risk of contamination with the same or different species, and we defined a cut-off of 30 heterozygous sites >50 bp apart to identify same-species contamination for MRSA. These metrics were combined into a quality-control (QC) flowchart to determine whether sequence runs and individual clinical isolates passed QC, which could be adapted by future automated analysis systems to enable rapid hands-off sequence analysis by clinical laboratories.

Evaluation of a fully automated bioinformatics tool to predict antibiotic resistance from MRSA genomes.

OBJECTIVES: The genetic prediction of phenotypic antibiotic resistance based on analysis of WGS data is becoming increasingly feasible, but a major barrier to its introduction into routine use is the lack of fully automated interpretation tools. Here, we report the findings of a large evaluation of the Next Gen Diagnostics (NGD) automated bioinformatics analysis tool to predict the phenotypic resistance of MRSA. METHODS: MRSA-positive patients were identified in a clinical microbiology laboratory in England between January and November 2018. One MRSA isolate per patient together with all blood culture isolates (total n = 778) were sequenced on the Illumina MiniSeq instrument in batches of 21 clinical MRSA isolates and three controls. RESULTS: The NGD system activated post-sequencing and processed the sequences to determine susceptible/resistant predictions for 11 antibiotics, taking around 11 minutes to analyse 24 isolates sequenced on a single sequencing run. NGD results were compared with phenotypic susceptibility testing performed by the clinical laboratory using the disc diffusion method and EUCAST breakpoints. Following retesting of discrepant results, concordance between phenotypic results and NGD genetic predictions was 99.69%. Further investigation of 22 isolate genomes associated with persistent discrepancies revealed a range of reasons in 12 cases, but no cause could be found for the remainder. Genetic predictions generated by the NGD tool were compared with predictions generated by an independent research-based informatics approach, which demonstrated an overall concordance between the two methods of 99.97%. CONCLUSIONS: We conclude that the NGD system provides rapid and accurate prediction of the antibiotic susceptibility of MRSA.

Pilot Evaluation of a Fully Automated Bioinformatics System for Analysis of Methicillin-Resistant Staphylococcus aureus Genomes and Detection of Outbreaks.

Genomic surveillance that combines bacterial sequencing and epidemiological information will become the gold standard for outbreak detection, but its clinical translation is hampered by the lack of automated interpretation tools. We performed a prospective pilot study to evaluate the analysis of methicillin-resistant Staphylococcus aureus (MRSA) genomes using the Next Gen Diagnostics (NGD) automated bioinformatics system. Seventeen unselected MRSA-positive patients were identified in a clinical microbiology laboratory in England over a period of 2 weeks in 2018, and 1 MRSA isolate per case was sequenced on the Illumina MiniSeq instrument. The NGD system automatically activated after sequencing and processed fastq folders to determine species, multilocus sequence type, the presence of a mec gene, antibiotic susceptibility predictions, and genetic relatedness based on mapping to a reference MRSA genome and detection of pairwise core genome single-nucleotide polymorphisms. The NGD system required 90 s per sample to automatically analyze data from each run, the results of which were automatically displayed. The same data were independently analyzed using a research-based approach. There was full concordance between the two analysis methods regarding species (S. aureus), detection of mecA, sequence type assignment, and detection of genetic determinants of resistance. Both analysis methods identified two MRSA clusters based on relatedness, one of which contained 3 cases that were involved in an outbreak linked to a clinic and ward associated with diabetic patient care. We conclude that, in this pilot study, the NGD system provided rapid and accurate data that could support infection control practices.

Rapid sequencing of MRSA direct from clinical plates in a routine microbiology laboratory.

BACKGROUND: Routine sequencing of MRSA could bring about significant improvements to outbreak detection and investigation. Sequencing is commonly performed using DNA extracted from a pure culture, but overcoming the delay associated with this step could reduce the time to infection control interventions. OBJECTIVES: To develop and evaluate rapid sequencing of MRSA using primary clinical cultures. METHODS: Patients with samples submitted to the clinical laboratory at the Cambridge University Hospitals NHS Foundation Trust from which MRSA was isolated were identified, the routine laboratory culture plates obtained and DNA extraction and sequencing performed. RESULTS: An evaluation of routine MRSA cultures from 30 patients demonstrated that direct sequencing from bacterial colonies picked from four different culture media was feasible. The 30 clinical MRSA isolates were sequenced on the day of plate retrieval over five runs and passed quality control metrics for sequencing depth and coverage. The maximum contamination detected using Kraken was 1.09% fragments, which were identified as Prevotella dentalis. The most common contaminants were other staphylococcal species (25 isolate sequences) and Burkholderia dolosa (11 isolate sequences). Core genome pairwise SNP analysis to identify clusters based on isolates that were ≤50 SNPs different was used to triage cases for further investigation. This identified three clusters, but more detailed genomic and epidemiological evaluation excluded an acute outbreak. CONCLUSIONS: Rapid sequencing of MRSA from clinical culture plates is feasible and reduces the delay associated with purity culture prior to DNA extraction.

Genomic surveillance of Escherichia coli in municipal wastewater treatment plants as an indicator of clinically relevant pathogens and their resistance genes.

We examined whether genomic surveillance of Escherichia coli in wastewater could capture the dominant E. coli lineages associated with bloodstream infection and livestock in the East of England, together with the antibiotic-resistance genes circulating in the wider E. coli population. Treated and untreated wastewater was taken from 20 municipal treatment plants in the East of England, half in direct receipt of acute hospital waste. All samples were culture positive for E. coli, and all but one were positive for extended-spectrum ß-lactamase (ESBL)-producing E. coli. The most stringent wastewater treatment (tertiary including UV light) did not eradicate ESBL-E. coli in 2/3 cases. We sequenced 388 E. coli (192 ESBL, 196 non-ESBL). Multilocus sequence type (ST) diversity was similar between plants in direct receipt of hospital waste versus the remainder (93 vs 95 STs, respectively). We compared the genomes of wastewater E. coli with isolates from bloodstream infection (n=437), and livestock farms and retail meat (n=431) in the East of England. A total of 19/20 wastewater plants contained one or more of the three most common STs associated with bloodstream infection (ST131, ST73, ST95), and 14/20 contained the most common livestock ST (ST10). In an analysis of 1254 genomes (2 cryptic E. coli were excluded), wastewater isolates were distributed across the phylogeny and intermixed with isolates from humans and livestock. Ten blaCTX-M elements were identified in E. coli isolated from wastewater, together with a further 47 genes encoding resistance to the major antibiotic drug groups. Genes encoding resistance to colistin and the carbapenems were not detected. Genomic surveillance of E. coli in wastewater could be used to monitor new and circulating lineages and resistance determinants of public-health importance.

Methodology for Whole-Genome Sequencing of Methicillin-Resistant Staphylococcus aureus Isolates in a Routine Hospital Microbiology Laboratory.

There is growing evidence for the value of bacterial whole-genome sequencing in hospital outbreak investigations. Our aim was to develop methods that support efficient and accurate low-throughput clinical sequencing of methicillin-resistant Staphylococcus aureus (MRSA) isolates. Using a test panel of 25 MRSA isolates previously associated with outbreak investigations, we devised modifications to library preparation that reduced the processing time by 1 hour. We determined the maximum number of isolates that could be sequenced per run using an Illumina MiniSeq platform and a 13-hour (overnight) run time, which equated to 21 MRSA isolates and 3 controls (no template, positive, and negative). Repeatability and reproducibility assays based on this sequencing methodology demonstrated 100% accuracy in assigning species and sequence type (ST) and in detecting mecA Established genetic relatedness between isolates was recapitulated. Quality control (QC) metrics were evaluated over nine sequencing runs. Of the test panel MRSA genomes, 168/173 (97%) passed QC metrics based on the correct species assigned, detection of mecA and ST, and depth/coverage metrics. An evaluation of contamination in these 9 runs showed that positive and negative controls and test MRSA sequence files contained <0.14% and <0.48% of fragments that matched another species, respectively. Deliberate contamination experiments confirmed that this was insufficient to impact data interpretation. These methods support reliable and reproducible clinical MRSA sequencing with a turnaround time (from DNA extraction to availability of data files) of 24 hours.

Detection of vancomycin-resistant Enterococcus faecium hospital-adapted lineages in municipal wastewater treatment plants indicates widespread distribution and release into the environment.

Vancomycin-resistant Enterococcus faecium (VREfm) is a leading cause of healthcare-associated infection. Reservoirs of VREfm are largely assumed to be nosocomial although there is a paucity of data on alternative sources. Here, we describe an integrated epidemiological and genomic analysis of E. faecium associated with bloodstream infection and isolated from wastewater. Treated and untreated wastewater from 20 municipal treatment plants in the East of England, United Kingdom was obtained and cultured to isolate E. faecium, ampicillin-resistant E. faecium (AREfm), and VREfm. VREfm was isolated from all 20 treatment plants and was released into the environment by 17/20 plants, the exceptions using terminal ultraviolet light disinfection. Median log10 counts of AREfm and VREfm in untreated wastewater from 10 plants in direct receipt of hospital sewage were significantly higher than 10 plants that were not. We sequenced and compared the genomes of 423 isolates from wastewater with 187 isolates associated with bloodstream infection at five hospitals in the East of England. Among 481 E. faecium isolates belonging to the hospital-adapted clade, we observed genetic intermixing between wastewater and bloodstream infection, with highly related isolates shared between a major teaching hospital in the East of England and 9/20 plants. We detected 28 antibiotic resistance genes in the hospital-adapted clade, of which 23 were represented in bloodstream, hospital sewage, and municipal wastewater isolates. We conclude that our findings are consistent with widespread distribution of hospital-adapted VREfm beyond acute healthcare settings with extensive release of VREfm into the environment in the East of England.

One Health Genomic Surveillance of Escherichia coli Demonstrates Distinct Lineages and Mobile Genetic Elements in Isolates from Humans versus Livestock.

Livestock have been proposed as a reservoir for drug-resistant Escherichia coli that infect humans. We isolated and sequenced 431 E. coli isolates (including 155 extended-spectrum ß-lactamase [ESBL]-producing isolates) from cross-sectional surveys of livestock farms and retail meat in the East of England. These were compared with the genomes of 1,517 E. coli bacteria associated with bloodstream infection in the United Kingdom. Phylogenetic core genome comparisons demonstrated that livestock and patient isolates were genetically distinct, suggesting that E. coli causing serious human infection had not directly originated from livestock. In contrast, we observed highly related isolates from the same animal species on different farms. Screening all 1,948 isolates for accessory genes encoding antibiotic resistance revealed 41 different genes present in variable proportions in human and livestock isolates. Overall, we identified a low prevalence of shared antimicrobial resistance genes between livestock and humans based on analysis of mobile genetic elements and long-read sequencing. We conclude that within the confines of our sampling framework, there was limited evidence that antimicrobial-resistant pathogens associated with serious human infection had originated from livestock in our region.IMPORTANCE The increasing prevalence of E. coli bloodstream infections is a serious public health problem. We used genomic epidemiology in a One Health study conducted in the East of England to examine putative sources of E. coli associated with serious human disease. E. coli from 1,517 patients with bloodstream infections were compared with 431 isolates from livestock farms and meat. Livestock-associated and bloodstream isolates were genetically distinct populations based on core genome and accessory genome analyses. Identical antimicrobial resistance genes were found in livestock and human isolates, but there was limited overlap in the mobile elements carrying these genes. Within the limitations of sampling, our findings do not support the idea that E. coli causing invasive disease or their resistance genes are commonly acquired from livestock in our region.

Genomic Surveillance of Enterococcus faecium Reveals Limited Sharing of Strains and Resistance Genes between Livestock and Humans in the United Kingdom.

Vancomycin-resistant Enterococcus faecium (VREfm) is a major cause of nosocomial infection and is categorized as high priority by the World Health Organization global priority list of antibiotic-resistant bacteria. In the past, livestock have been proposed as a putative reservoir for drug-resistant E. faecium strains that infect humans, and isolates of the same lineage have been found in both reservoirs. We undertook cross-sectional surveys to isolate E. faecium (including VREfm) from livestock farms, retail meat, and wastewater treatment plants in the United Kingdom. More than 600 isolates from these sources were sequenced, and their relatedness and antibiotic resistance genes were compared with genomes of almost 800 E. faecium isolates from patients with bloodstream infection in the United Kingdom and Ireland. E. faecium was isolated from 28/29 farms; none of these isolates were VREfm, suggesting a decrease in VREfm prevalence since the last UK livestock survey in 2003. However, VREfm was isolated from 1% to 2% of retail meat products and was ubiquitous in wastewater treatment plants. Phylogenetic comparison demonstrated that the majority of human and livestock-related isolates were genetically distinct, although pig isolates from three farms were more genetically related to human isolates from 2001 to 2004 (minimum of 50 single-nucleotide polymorphisms [SNPs]). Analysis of accessory (variable) genes added further evidence for distinct niche adaptation. An analysis of acquired antibiotic resistance genes and their variants revealed limited sharing between humans and livestock. Our findings indicate that the majority of E. faecium strains infecting patients are largely distinct from those from livestock in this setting, with limited sharing of strains and resistance genes.IMPORTANCE The rise in rates of human infection caused by vancomycin-resistant Enterococcus faecium (VREfm) strains between 1988 to the 2000s in Europe was suggested to be associated with acquisition from livestock. As a result, the European Union banned the use of the glycopeptide drug avoparcin as a growth promoter in livestock feed. While some studies reported a decrease in VREfm in livestock, others reported no reduction. Here, we report the first livestock VREfm prevalence survey in the UK since 2003 and the first large-scale study using whole-genome sequencing to investigate the relationship between E. faecium strains in livestock and humans. We found a low prevalence of VREfm in retail meat and limited evidence for recent sharing of strains between livestock and humans with bloodstream infection. There was evidence for limited sharing of genes encoding antibiotic resistance between these reservoirs, a finding which requires further research.

Duration of exposure to multiple antibiotics is associated with increased risk of VRE bacteraemia: a nested case-control study.

Background: VRE bacteraemia has a high mortality and continues to defy control. Antibiotic risk factors for VRE bacteraemia have not been adequately defined. We aimed to determine the risk factors for VRE bacteraemia focusing on duration of antibiotic exposure. Methods: A retrospective matched nested case-control study was conducted amongst hospitalized patients at Cambridge University Hospitals NHS Foundation Trust (CUH) from 1 January 2006 to 31 December 2012. Cases who developed a first episode of VRE bacteraemia were matched 1:1 to controls by length of stay, year, specialty and ward type. Independent risk factors for VRE bacteraemia were evaluated using conditional logistic regression. Results: Two hundred and thirty-five cases were compared with 220 controls. Duration of exposure to parenteral vancomycin, fluoroquinolones and meropenem was independently associated with VRE bacteraemia. Compared with patients with no exposure to vancomycin, those who received courses of 1-3 days, 4-7 days or >7 days had a stepwise increase in risk of VRE bacteraemia [conditional OR (cOR) 1.2 (95% CI 0.4-3.8), 3.8 (95% CI 1.2-11.7) and 6.6 (95% CI 1.9-22.8), respectively]. Other risk factors were: presence of a central venous catheter (CVC) [cOR 8.7 (95% CI 2.6-29.5)]; neutropenia [cOR 15.5 (95% CI 4.2-57.0)]; hypoalbuminaemia [cOR 8.5 (95% CI 2.4-29.5)]; malignancy [cOR 4.4 (95% CI 1.6-12.0)]; gastrointestinal disease [cOR 12.4 (95% CI 4.2-36.8)]; and hepatobiliary disease [cOR 7.9 (95% CI 2.1-29.9)]. Conclusions: Longer exposure to vancomycin, fluoroquinolones or meropenem was associated with VRE bacteraemia. Antimicrobial stewardship interventions targeting high-risk antibiotics are required to complement infection control procedures against VRE bacteraemia.

Genome-Based Analysis of Enterococcus faecium Bacteremia Associated with Recurrent and Mixed-Strain Infection.

Vancomycin-resistant Enterococcus faecium (VREfm) bloodstream infections are associated with high recurrence rates. This study used genome sequencing to accurately distinguish the frequency of relapse and reinfection in patients with recurrent E. faecium bacteremia and to investigate strain relatedness in patients with apparent VREfm and vancomycin-susceptible E. faecium (VSEfm) mixed infection. A retrospective study was performed at the Cambridge University Hospitals NHS Foundation Trust (CUH) between November 2006 and December 2012. We analyzed the genomes of 44 E. faecium isolates from 21 patients (26 VREfm isolates from 12 patients with recurrent bacteremia and 18 isolates from 9 patients with putative VREfm/VSEfm mixed infection). Phenotypic antibiotic susceptibility was determined using a Vitek2 instrument. Genomes were compared with those of a further 263 E. faecium isolates associated with bacteremia in patients at CUH over the same time period. Pairwise comparison of core genomes indicated that 10 (71%) episodes of recurrent VREfm bacteremia were due to reinfection with a new strain, with reinfection being more likely with increasing time between the two positive cultures. The majority (78%) of patients with a mixed VREfm and VSEfm infection had unrelated strains. More than half (59%) of study isolates were closely related to another isolate associated with bacteremia from CUH. This included 60% of isolates associated with reinfection, indicating acquisition in the hospital. This study provides the first high-resolution insights into recurrence and mixed infection by E. faecium and demonstrates that reinfection with a new strain, often acquired from the hospital, is a driver of recurrence.

Longitudinal genomic surveillance of MRSA in the UK reveals transmission patterns in hospitals and the community.

Genome sequencing has provided snapshots of the transmission of methicillin-resistant Staphylococcus aureus (MRSA) during suspected outbreaks in isolated hospital wards. Scale-up to populations is now required to establish the full potential of this technology for surveillance. We prospectively identified all individuals over a 12-month period who had at least one MRSA-positive sample processed by a routine diagnostic microbiology laboratory in the East of England, which received samples from three hospitals and 75 general practitioner (GP) practices. We sequenced at least 1 MRSA isolate from 1465 individuals (2282 MRSA isolates) and recorded epidemiological data. An integrated epidemiological and phylogenetic analysis revealed 173 transmission clusters containing between 2 and 44 cases and involving 598 people (40.8%). Of these, 118 clusters (371 people) involved hospital contacts alone, 27 clusters (72 people) involved community contacts alone, and 28 clusters (157 people) had both types of contact. Community- and hospital-associated MRSA lineages were equally capable of transmission in the community, with instances of spread in households, long-term care facilities, and GP practices. Our study provides a comprehensive picture of MRSA transmission in a sampled population of 1465 people and suggests the need to review existing infection control policy and practice.