Efficacy of ChAdOx1 nCoV-19 (AZD1222) vaccine against SARS-CoV-2 variant of concern 202012/01 (B.1.1.7): an exploratory analysis of a randomised controlled trial.

BACKGROUND: A new variant of SARS-CoV-2, B.1.1.7, emerged as the dominant cause of COVID-19 disease in the UK from November, 2020. We report a post-hoc analysis of the efficacy of the adenoviral vector vaccine, ChAdOx1 nCoV-19 (AZD1222), against this variant. METHODS: Volunteers (aged ≥18 years) who were enrolled in phase 2/3 vaccine efficacy studies in the UK, and who were randomly assigned (1:1) to receive ChAdOx1 nCoV-19 or a meningococcal conjugate control (MenACWY) vaccine, provided upper airway swabs on a weekly basis and also if they developed symptoms of COVID-19 disease (a cough, a fever of 37·8°C or higher, shortness of breath, anosmia, or ageusia). Swabs were tested by nucleic acid amplification test (NAAT) for SARS-CoV-2 and positive samples were sequenced through the COVID-19 Genomics UK consortium. Neutralising antibody responses were measured using a live-virus microneutralisation assay against the B.1.1.7 lineage and a canonical non-B.1.1.7 lineage (Victoria). The efficacy analysis included symptomatic COVID-19 in seronegative participants with a NAAT positive swab more than 14 days after a second dose of vaccine. Participants were analysed according to vaccine received. Vaccine efficacy was calculated as 1 - relative risk (ChAdOx1 nCoV-19 vs MenACWY groups) derived from a robust Poisson regression model. This study is continuing and is registered with ClinicalTrials.gov, NCT04400838, and ISRCTN, 15281137. FINDINGS: Participants in efficacy cohorts were recruited between May 31 and Nov 13, 2020, and received booster doses between Aug 3 and Dec 30, 2020. Of 8534 participants in the primary efficacy cohort, 6636 (78%) were aged 18-55 years and 5065 (59%) were female. Between Oct 1, 2020, and Jan 14, 2021, 520 participants developed SARS-CoV-2 infection. 1466 NAAT positive nose and throat swabs were collected from these participants during the trial. Of these, 401 swabs from 311 participants were successfully sequenced. Laboratory virus neutralisation activity by vaccine-induced antibodies was lower against the B.1.1.7 variant than against the Victoria lineage (geometric mean ratio 8·9, 95% CI 7·2-11·0). Clinical vaccine efficacy against symptomatic NAAT positive infection was 70·4% (95% CI 43·6-84·5) for B.1.1.7 and 81·5% (67·9-89·4) for non-B.1.1.7 lineages. INTERPRETATION: ChAdOx1 nCoV-19 showed reduced neutralisation activity against the B.1.1.7 variant compared with a non-B.1.1.7 variant in vitro, but the vaccine showed efficacy against the B.1.1.7 variant of SARS-CoV-2. FUNDING: UK Research and Innovation, National Institute for Health Research (NIHR), Coalition for Epidemic Preparedness Innovations, NIHR Oxford Biomedical Research Centre, Thames Valley and South Midlands NIHR Clinical Research Network, and AstraZeneca.

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.

Significant variability exists in the cytotoxicity of global methicillin-resistant Staphylococcus aureus lineages.

Staphylococcus aureus is a major human pathogen where the emergence of antibiotic resistant lineages, such as methicillin-resistant S. aureus (MRSA), is a major health concern. While some MRSA lineages are restricted to the healthcare setting, the epidemiology of MRSA is changing globally, with the rise of specific lineages causing disease in healthy people in the community. In the past two decades, community-associated MRSA (CA-MRSA) has emerged as a clinically important and virulent pathogen associated with serious skin and soft-tissue infections (SSTI). These infections are primarily cytotoxin driven, leading to the suggestion that hypervirulent lineages/multi-locus sequence types (STs) exist. To examine this, we compared the cytotoxicity of 475 MRSA isolates representing five major MRSA STs (ST22, ST93, ST8, ST239 and ST36) by employing a monocyte-macrophage THP-1 cell line as a surrogate for measuring gross cytotoxicity. We demonstrate that while certain MRSA STs contain highly toxic isolates, there is such variability within lineages to suggest that this aspect of virulence should not be inferred from the genotype of any given isolate. Furthermore, by interrogating the accessory gene regulator (Agr) sequences in this collection we identified several Agr mutations that were associated with reduced cytotoxicity. Interestingly, the majority of isolates that were attenuated in cytotoxin production contained no mutations in the agr locus, indicating a role of other undefined genes in S. aureus toxin regulation.

A One Health Study of the Genetic Relatedness of Klebsiella pneumoniae and Their Mobile Elements in the East of England.

BACKGROUND: Klebsiella pneumoniae is a human, animal, and environmental commensal and a leading cause of nosocomial infections, which are often caused by multiresistant strains. We evaluate putative sources of K. pneumoniae that are carried by and infect hospital patients. METHODS: We conducted a 6-month survey on 2 hematology wards at Addenbrooke's Hospital, Cambridge, United Kingdom, in 2015 to isolate K. pneumoniae from stool, blood, and the environment. We conducted cross-sectional surveys of K. pneumoniae from 29 livestock farms, 97 meat products, the hospital sewer, and 20 municipal wastewater treatment plants in the East of England between 2014 and 2015. Isolates were sequenced and their genomes compared. RESULTS: Klebsiella pneumoniae was isolated from stool of 17/149 (11%) patients and 18/922 swabs of their environment, together with 1 bloodstream infection during the study and 4 others over a 24-month period. Each patient carried 1 or more lineages that was unique to them, but 2 broad environmental contamination events and patient-environment transmission were identified. Klebsiella pneumoniae was isolated from cattle, poultry, hospital sewage, and 12/20 wastewater treatment plants. There was low genetic relatedness between isolates from patients/their hospital environment vs isolates from elsewhere. Identical genes encoding cephalosporin resistance were carried by isolates from humans/environment and elsewhere but were carried on different plasmids. CONCLUSION: We identified no patient-to-patient transmission and no evidence for livestock as a source of K. pneumoniae infecting humans. However, our findings reaffirm the importance of the hospital environment as a source of K. pneumoniae associated with serious human infection.

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.

Building a genomic framework for prospective MRSA surveillance in the United Kingdom and the Republic of Ireland.

The correct interpretation of microbial sequencing data applied to surveillance and outbreak investigation depends on accessible genomic databases to provide vital genetic context. Our aim was to construct and describe a United Kingdom MRSA database containing over 1000 methicillin-resistant Staphylococcus aureus (MRSA) genomes drawn from England, Northern Ireland, Wales, Scotland, and the Republic of Ireland over a decade. We sequenced 1013 MRSA submitted to the British Society for Antimicrobial Chemotherapy by 46 laboratories between 2001 and 2010. Each isolate was assigned to a regional healthcare referral network in England and was otherwise grouped based on country of origin. Phylogenetic reconstructions were used to contextualize MRSA outbreak investigations and to detect the spread of resistance. The majority of isolates (n = 783, 77%) belonged to CC22, which contains the dominant United Kingdom epidemic clone (EMRSA-15). There was marked geographic structuring of EMRSA-15, consistent with widespread dissemination prior to the sampling decade followed by local diversification. The addition of MRSA genomes from two outbreaks and one pseudo-outbreak demonstrated the certainty with which outbreaks could be confirmed or refuted. We identified local and regional differences in antibiotic resistance profiles, with examples of local expansion, as well as widespread circulation of mobile genetic elements across the bacterial population. We have generated a resource for the future surveillance and outbreak investigation of MRSA in the United Kingdom and Ireland and have shown the value of this during outbreak investigation and tracking of antimicrobial resistance.

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.

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.

Prospective genomic surveillance of methicillin-resistant Staphylococcus aureus (MRSA) associated with bloodstream infection, England, 1 October 2012 to 30 September 2013.

BackgroundMandatory reporting of methicillin-resistant Staphylococcus aureus (MRSA) bloodstream infections (BSI) has occurred in England for over 15years. Epidemiological information is recorded, but routine collection of isolates for characterisation has not been routinely undertaken. Ongoing developments in whole-genome sequencing (WGS) have demonstrated its value in outbreak investigations and for determining the spread of antimicrobial resistance and bacterial population structure. Benefits of adding genomics to routine epidemiological MRSA surveillance are unknown.AimTo determine feasibility and potential utility of adding genomics to epidemiological surveillance of MRSA.MethodsWe conducted an epidemiological and genomic survey of MRSA BSI in England over a 1-year period (1 October 2012--30 September 2013).ResultsDuring the study period, 903 cases of MRSA BSI were reported; 425 isolates were available for sequencing of which, 276 (65%) were clonal complex (CC) 22. Addition of 64 MRSA genomes from published outbreak investigations showed that the study genomes could provide context for outbreak isolates and supported cluster identification. Comparison to other MRSA genome collections demonstrated variation in clonal diversity achieved through different sampling strategies and identified potentially high-risk clones e.g. USA300 and local expansion of CC5 MRSA in South West England.ConclusionsWe demonstrate the potential utility of combined epidemiological and genomic MRSA BSI surveillance to determine the national population structure of MRSA, contextualise previous MRSA outbreaks, and detect potentially high-risk lineages. These findings support the integration of epidemiological and genomic surveillance for MRSA BSI as a step towards a comprehensive surveillance programme in England.

Investigation of a Cluster of Sequence Type 22 Methicillin-Resistant Staphylococcus aureus Transmission in a Community Setting.

BACKGROUND: Whole-genome sequencing (WGS) has typically been used to confirm or refute hospital/ward outbreaks of methicillin-resistant Staphylococcus aureus (MRSA) identified through routine practice. However, appropriately targeted WGS strategies that identify routinely "undetectable" transmission remain the ultimate aim. METHODS: WGS of MRSA isolates sent to a regional microbiological laboratory was performed as part of a 12-month prospective observational study. Phylogenetic analyses identified a genetically related cluster of E-MRSA15 isolated from patients registered to the same general practice (GP) surgery. This led to an investigation to identify epidemiological links, find additional cases, and determine potential for ongoing transmission. RESULTS: We identified 15 MRSA-positive individuals with 27 highly related MRSA isolates who were linked to the GP surgery, 2 of whom died with MRSA bacteremia. Of the 13 cases that were further investigated, 11 had attended a leg ulcer/podiatry clinic. Cases lacked epidemiological links to hospitals, suggesting that transmission occurred elsewhere. Environmental and staff screening at the GP surgery did not identify an ongoing source of infection. CONCLUSIONS: Surveillance in the United Kingdom shows that the proportion of MRSA bacteremias apportioned to hospitals is decreasing, suggesting the need for greater focus on the detection of MRSA outbreaks and transmission in the community. This case study confirms that the typically nosocomial lineage (E-MRSA15) can transmit within community settings. Our study exemplifies the continued importance of WGS in detecting outbreaks, including those which may be missed by routine practice, and suggests that universal WGS of bacteremia isolates may help detect outbreaks in low-surveillance settings.

Systematic Surveillance Detects Multiple Silent Introductions and Household Transmission of Methicillin-Resistant Staphylococcus aureus USA300 in the East of England.

BACKGROUND: The spread of USA300 methicillin-resistant Staphylococcus aureus (MRSA) across the United States resulted in an epidemic of infections. In Europe, only sporadic cases or small clusters of USA300 infections are described, and its prevalence in England is unknown. We conducted prospective surveillance for USA300 in the east of England. METHODS: We undertook a 12-month prospective observational cohort study of all individuals with MRSA isolated from community and hospital samples submitted to a microbiology laboratory. At least 1 MRSA isolate from each individual underwent whole-genome sequencing. USA300 was identified on the basis of sequence analysis, and phylogenetic comparisons were made between these and USA300 genomes from the United States. RESULTS: Between April 2012 and April 2013, we sequenced 2283 MRSA isolates (detected during carriage screening and in clinical samples) from 1465 individuals. USA300 was isolated from 24 cases (1.6%). Ten cases (42%) had skin and soft tissue infection, and 2 cases had invasive disease. Phylogenetic analyses identified multiple introductions and household transmission of USA300. CONCLUSIONS: Use of a diagnostic laboratory as a sentinel for surveillance has identified repeated introductions of USA300 in eastern England in 2012-2013, with evidence for limited transmission. Our results show how systematic surveillance could provide an early warning of strain emergence and dissemination.

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.

Evolution and host-specific adaptation of Pseudomonas aeruginosa.

The major human bacterial pathogen Pseudomonas aeruginosa causes multidrug-resistant infections in people with underlying immunodeficiencies or structural lung diseases such as cystic fibrosis (CF). We show that a few environmental isolates, driven by horizontal gene acquisition, have become dominant epidemic clones that have sequentially emerged and spread through global transmission networks over the past 200 years. These clones demonstrate varying intrinsic propensities for infecting CF or non-CF individuals (linked to specific transcriptional changes enabling survival within macrophages); have undergone multiple rounds of convergent, host-specific adaptation; and have eventually lost their ability to transmit between different patient groups. Our findings thus explain the pathogenic evolution of P. aeruginosa and highlight the importance of global surveillance and cross-infection prevention in averting the emergence of future epidemic clones.

Dissemination of carbapenemase-producing Enterobacterales in Ireland from 2012 to 2017: a retrospective genomic surveillance study.

The spread of carbapenemase-producing Enterobacterales (CPE) is of major public health concern. The transmission dynamics of CPE in hospitals, particularly at the national level, are not well understood. Here, we describe a retrospective nationwide genomic surveillance study of CPE in Ireland between 2012 and 2017. We sequenced 746 national surveillance CPE samples obtained between 2012 and 2017. After clustering the sequences, we used thresholds based on pairwise SNPs, and reported within-host diversity along with epidemiological data to infer recent putative transmissions. All clusters in circulating clones, derived from high-resolution phylogenies, of a species (Klebsiella pneumoniae, Escherichia coli, Klebsiella oxytoca, Enterobacter cloacae, Enterobacter hormaechei and Citrobacter freundii) were individually examined for evidence of transmission. Antimicrobial resistance trends over time were also assessed. We identified 352 putative transmission events in six species including widespread and frequent transmissions in three species. We detected putative outbreaks in 4/6 species with three hospitals experiencing prolonged outbreaks. The bla OXA-48 gene was the main cause of carbapenem resistance in Ireland in almost all species. An expansion in the number of sequence types carrying bla OXA-48 was an additional cause of the increasing prevalence of carbapenemase-producing K. pneumoniae and E. coli.

The clinical, genomic, and microbiological profile of invasive multi-drug resistant Escherichia coli in a major teaching hospital in the United Kingdom.

Escherichia coli is a ubiquitous component of the human gut microbiome, but is also a common pathogen, causing around 40, 000 bloodstream infections (BSI) in the United Kingdom (UK) annually. The number of E. coli BSI has increased over the last decade in the UK, and emerging antimicrobial resistance (AMR) profiles threaten treatment options. Here, we combined clinical, epidemiological, and whole genome sequencing data with high content imaging to characterise over 300 E. coli isolates associated with BSI in a large teaching hospital in the East of England. Overall, only a limited number of sequence types (ST) were responsible for the majority of organisms causing invasive disease. The most abundant (20 % of all isolates) was ST131, of which around 90 % comprised the pandemic O25b:H4 group. ST131-O25b:H4 isolates were frequently multi-drug resistant (MDR), with a high prevalence of extended spectrum ß-lactamases (ESBL) and fluoroquinolone resistance. There was no association between AMR phenotypes and the source of E. coli bacteraemia or whether the infection was healthcare-associated. Several clusters of ST131 were genetically similar, potentially suggesting a shared transmission network. However, there was no clear epidemiological associations between these cases, and they included organisms from both healthcare-associated and non-healthcare-associated origins. The majority of ST131 isolates exhibited strong binding with an anti-O25b antibody, raising the possibility of developing rapid diagnostics targeting this pathogen. In summary, our data suggest that a restricted set of MDR E. coli populations can be maintained and spread across both community and healthcare settings in this location, contributing disproportionately to invasive disease and AMR.

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.