Zero tolerance for healthcare-associated MRSA bacteraemia: is it realistic?

Preventing healthcare-associated MRSA bacteremia: getting to the root of the problem

Introduction

Bloodstream infections caused by methicillin-resistant Staphylococcus aureus (MRSA) remain a major challenge in most countries worldwide.

Setting

We describe a quasi-experimental sequential intervention at Mater Dei Hospital, Malta, to reduce hyper-prevalence of healthcare-associated MRSA bacteremia (HA-MRSA-B).

Interventions

The hospital initiated a hand hygiene (HH) campaign in 2008 to improve alcohol hand rub (AHR) use. In 2011, this was followed by root cause analysis (RCA) of all HA-MRSA-B cases and finally universal MRSA admission screening in 2014. Change-point analysis was used to evaluate the impact of the interventions.

Results

The effect of the HH campaign became evident when AHR consumption reached 40 L/1000 occupied bed days (BD). RCAs identified intravascular devices as the likely risk factor in 83% of all HA-MRSA-B; specifically non-tunneled double-lumen hemodialysis catheters (36%), peripheral venous cannulas (25%), and central venous catheters (22%). Interventions to improve their management resulted in the greatest reduction of HA-MRSA-B rates. They were informed by the RCA findings and targeted behavior change through education, motivation, and system change. Universal MRSA admission screening provided the final decline in incidence. Each intervention affected HA-MRSA-B rates after a lag period of approximately 18-24 months. Overall, HA-MRSA-B incidence decreased from 1.72 cases/10000BD in 2008 to 0.18/10000BD in 2019; a reduction of almost 90%. Intravenous device interventions were also associated with a reduction of methicillin-sensitive Staphylococcus aureus (MSSA) bacteremia rates.

Conclusions

Significant improvement in HA-MRSA-B is possible, even in highly endemic regions. It requires well-planned behavior change interventions which are compatible with local context and culture.

Whole genome sequencing reveals new links between spa t172/CC59 methicillin-resistant Staphylococcus aureus cases in low-endemicity region of Southwest Finland, 2007‒2016

Methicillin-resistant Staphylococcus aureus (MRSA) rates have remained relatively low in Finland. In Southwest Finland, however, annual MRSA incidence increased from 12 to 25/100,000 between 2007 and 2016 with spa t172 strain causing one fourth (237/983) of all cases. This provoked us to study the molecular epidemiology of t172-MRSA, aiming to better understand the transmission of this strain type. We combined epidemiological data and whole genome sequencing (WGS) of a set of 64 (27%, 64/237) t172-MRSA isolates covering 10 years. Isolates represented sporadic and index cases of all identified healthcare-associated outbreaks (HAOs) and family clusters (FCs). Among the included 62 isolates, core-genome MLST analysis revealed eight genomic clusters comprising 24 (38.7%) isolates and 38 (61.3%) non-clustered isolates. Cluster 1 comprised ten and the remaining seven clusters two isolates each, respectively. Two epidemiologically distinct HAOs were linked in cluster 1. FCs were involved in all clusters. All strains were associated with epidemic clonal complex CC59. We were able to confirm the spread of several successful t172-MRSA subclones in regional healthcare and the community. WGS complemented routine surveillance by revealing undetected links between t172-MRSA cases. Targeted, WGS-based typing could enhance MRSA surveillance without the need for routine WGS diagnostics.

Genomic Epidemiology and Characterization of Methicillin-Resistant Staphylococcus aureus from Bloodstream Infections in China

Since 2010, methicillin-resistant Staphylococcus aureus (MRSA) ST59 began to increase in prevalence in China, gradually replacing ST239 and has become the dominant clone in most hospitals in China. Here, we investigated the changing epidemiology, phylogenetic reconstruction, and genomic characterization of MRSA clones in China to identify the genomic driving factors in the prevalence of ST59. Most MRSA isolates were identified as ST59 (36.98%; 277/749), which increased from 25.09% in 2014 to 35.53% in 2019. The phylogenetic analysis of the 749 MRSA isolates showed a high level of diversity and the copresence of hospital-associated, community-associated, livestock-associated, and hypervirulent clones. Furthermore, minimum spanning trees revealed that ST59 MRSA clones from different hospitals and regions were integrated, suggesting that frequent exchanges had occurred between regions and hospitals. ST59 clones displayed higher susceptibility to antimicrobials than did ST239 and ST5 MRSA clones, indicating that resistance to non-β-lactam and fluoroquinolone antibiotics may be not critical for the epidemic success of ST59 clones. Virulence factors detection showed that sak and chp genes enriched in MRSA ST59 may be associated with the enhanced spreading success of ST59, whereas qacA may have contributed to the predominance of ST5 in East China. Our refined analysis of different clones among ST239, ST5, ST59, and ST398 demonstrated the existence of potential driving factors for the evolution of nosocomial MRSA populations and diversity of the evolutionary events surrounding clonal replacement.

IMPORTANCE As a developing country, China has an unbalanced health care system due to regional differences in economic development. However, China is also a country worthy of study with regard to the population dynamics of MRSA within the more resource-rich health care systems. In this study, we carried out genomic analysis to investigate the genomic epidemiology and characterization of MRSA isolated from bloodstream infections over a timespan of 6 years. Our refined analysis of different MRSA clones among ST59, ST5, ST239, and ST398 demonstrated the existence of driving factors for the evolution of nosocomial MRSA populations and diversity of the evolutionary events surrounding clonal replacement.

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.

Development and piloting of a prevention assessment and response tool for healthcare-associated Staphylococcus aureus bloodstream infection (the SAB-PART Study) using a Delphi method

BACKGROUND

Healthcare-associated Staphylococcus aureus bloodstream infection (HA-SAB) causes preventable harm in hospitalized patients. Currently, there is no standardized method available to review HA-SAB events in order to identify and target preventable risks requiring action at an organizational level.

AIM

To develop a tool to classify SAB events, and the necessary response actions, according to the degree of preventability.

METHODS

Following a literature review, a tool was developed. Consensus feedback and development of the tool was sought from experts (N = 11) in healthcare-associated infection surveillance using a Delphi technique. The completed tool was retrospectively applied to HA-SAB events (N = 43) that occurred at a large healthcare organization.

FINDINGS

Survey completion rates were high (91-100%). Clinicians' poor adherence to infection prevention practices and lack of engagement with feedback processes was established as the key modifiable element. A second key theme was the need for structured and detailed response actions. This feedback was incorporated into the tool and refined until consensus on all elements was achieved. Pilot application of the tool found that 56% of HA-SAB events were highly or possibly preventable; modifiable factors for HA-SAB prevention were not present in the remainder of cases.

CONCLUSION

A prevention assessment and response tool was successfully developed via a consensus method to assist organizations in investigating and responding to individual cases of HA-SAB and identify future priority areas for SAB reduction strategies. Wider use of the tool with routine surveillance activities is required to evaluate impact upon infection prevention programmes and patient outcomes.

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.

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.

Clonal expansion of community-associated meticillin-resistant Staphylococcus aureus (MRSA) in people who inject drugs (PWID): prevalence, risk factors and molecular epidemiology, Bristol, United Kingdom, 2012 to 2017

Background: In 2015, Bristol (South West England) experienced a large increase in cases of meticillin-resistant Staphylococcus aureus (MRSA) infection in people who inject drugs (PWID).

Aim: We aimed to characterise and estimate the prevalence of MRSA colonisation among PWID in Bristol and test evidence of a clonal outbreak.

Methods: PWID recruited through an unlinked-anonymous community survey during 2016 completed behavioural questionnaires and were screened for MRSA. Univariable logistic regression examined associations with MRSA colonisation. Whole-genome sequencing used lineage-matched MRSA isolates, comparing PWID (screening and retrospective bacteraemia samples from 2012-2017) with non-PWID (Bristol screening) in Bristol and national reference laboratory database samples.

Results: The MRSA colonisation prevalence was 8.7% (13/149) and was associated with frequently injecting in public places (odds ratio (OR): 5.5; 95% confidence interval (CI):1.34–22.70), recent healthcare contact (OR: 4.3; 95% CI: 1.34–13.80) and injecting in groups of three or more (OR: 15.8; 95% CI: 2.51–99.28). People reporting any one of: injecting in public places, injection site skin and soft tissue infection or hospital contact accounted for 12/13 MRSA positive cases (sensitivity 92.3%; specificity 51.5%). Phylogenetic analysis identified a dominant clade associated with infection and colonisation among PWID in Bristol belonging to ST5-SCCmecIVg.

Conclusions: MRSA colonisation in Bristol PWID is substantially elevated compared with general population estimates and there is evidence of clonal expansion, community-based transmission and increased infection risk related to the colonising strain. Targeted interventions, including community screening and suppression therapy, education and basic infection control are needed to reduce MRSA infections in PWID.

Genomic Surveillance of Methicillin-resistant Staphylococcus aureus: A Mathematical Early Modeling Study of Cost-effectiveness

BACKGROUND

Genomic surveillance of methicillin-resistant Staphylococcus aureus (MRSA) identifies unsuspected transmission events and outbreaks. Used proactively, this could direct early and highly targeted infection control interventions to prevent ongoing spread. Here, we evaluated the cost-effectiveness of this intervention in a model that compared whole-genome sequencing plus current practice versus current practice alone.

METHODS

A UK cost-effectiveness study was conducted using an early model built from the perspective of the National Health Service and personal social services. The effectiveness of sequencing was based on the relative reduction in total MRSA acquisitions in a cohort of hospitalized patients in the year following their index admissions. A sensitivity analysis was used to illustrate and assess the level of confidence associated with the conclusions of our economic evaluation.

RESULTS

A cohort of 65 000 patients were run through the model. Assuming that sequencing would result in a 90% reduction in MRSA acquisition, 290 new MRSA cases were avoided. This gave an absolute reduction of 28.8% and avoidance of 2 MRSA-related deaths. Base case results indicated that the use of routine, proactive MRSA sequencing would be associated with estimated cost savings of over £728 290 per annual hospitalized cohort. The impact in total quality-adjusted life years (QALYs) was relatively modest, with sequencing leading to an additional 14.28 QALYs gained. Results were most sensitive to changes in the probability of a MRSA-negative patient acquiring MRSA during their hospital admission.

CONCLUSIONS

We showed that proactive genomic surveillance of MRSA is likely to be cost-effective. Further evaluation is required in the context of a prospective study.

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.

Presentation and outcomes of end stage liver disease patients presenting with septic shock to the emergency department

BACKGROUND

Patients with end stage liver disease (ESLD) are particularly vulnerable to sepsis. ESLD patients are often excluded from controlled sepsis trials and more data are needed to guide the management of this population.

OBJECTIVE

To describe the clinical factors and outcomes of patients with ESLD presenting to the emergency department (ED) with septic shock.

METHODS

We performed a retrospective review of patients registered in our dedicated ED adult septic shock pathway. All patients registered between January 2014 and May 2016 were included. Clinical and treatment variables for ESLD patients were compared with non-ESLD patients. A second analysis assessed ESLD survivors compared to non-survivors.

RESULTS

2,584 septic shock patients were enrolled. ESLD was present in 6.2% (n = 161) of patients. Patients with ESLD had higher mortality compared to patients without ESLD 36.6% vs 21.2% (p < 0.001). ESLD patients were more likely to be younger, female, obese, and have other comorbidities. ESLD patients exhibited lower temperature, higher lactate, and higher incidence of acute kidney injury. There was no difference in antibiotics or fluid resuscitation between groups. ESLD patients received more ED vasopressor support. Among ESLD septic shock patients, maximum lactate and presence of pneumonia were independently associated with death.

CONCLUSIONS

Patients with ESLD comprise a small but important subgroup of patients with ED septic shock that experience high mortality compared to patients without ESLD. Maximum ED lactate and pneumonia as the source of sepsis are independently associated with adverse outcome and may be used for early recognition of high-risk ESLD sepsis patients.

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.

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.

Frequent Undetected Ward-Based Methicillin-Resistant Staphylococcus aureus Transmission Linked to Patient Sharing Between Hospitals

Background

Recent evidence suggests that hospital transmission of methicillin-resistant Staphylococcus aureus (MRSA) is uncommon in UK centers that have implemented sustained infection control programs. We investigated whether a healthcare-network analysis could shed light on transmission paths currently sustaining MRSA levels in UK hospitals.

Methods

A cross-sectional observational study was performed in 2 National Health Service hospital groups and a general district hospital in Southeast London. All MRSA patients identified at inpatient, outpatient, and community settings between 1 November 2011 and 29 February 2012 were included. We identified genetically defined MRSA transmission clusters in individual hospitals and across the healthcare network, and examined genetic differentiation of sequence type (ST) 22 MRSA isolates within and between hospitals and inpatient or outpatient and community settings, as informed by average and median pairwise single-nucleotide polymorphisms (SNPs) and SNP-based proportions of nearly identical isolates.

Results

Two hundred forty-eight of 610 (40.7%) MRSA patients were linked in 90 transmission clusters, of which 27 spanned multiple hospitals. Analysis of a large 32 patient ST22-MRSA cluster showed that 26 of 32 patients (81.3%) had multiple contacts with one another during ward stays at any hospital. No residential, outpatient, or significant community healthcare contacts were identified. Genetic differentiation between ST22 MRSA inpatient isolates from different hospitals was less than between inpatient isolates from the same hospitals (P ≤ .01).

Conclusions

There is evidence of frequent ward-based transmission of MRSA brought about by frequent patient admissions to multiple hospitals. Limiting in-ward transmission requires sharing of MRSA status data between hospitals.

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.

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.

The value of the infection prevention and control nurse led MRSA ward round

Meticillin-resistant S. aureus (MRSA) is prevalent in most parts of the world. The study took place at Queen Elizabeth Hospital Birmingham (QEHB) a UK tertiary referral hospital. At QEHB innovative nurse led daily ward rounds for patients that acquire hospital acquired MRSA during their hospital stay are undertaken. The aim is to optimise care delivered for these patients whilst at QEHB, thereby reducing the risk of infection in patients with healthcare-acquired MRSA. A segmented Poisson regression model suggests that the MRSA bacteraemia rate was affected where an 88.94% reduction (p = 0.0561) in bacteraemias was seen by the introduction of these ward rounds. We describe a nurse led MRSA ward round which was associated with a lower rate of MRSA bacteraemias.

Changing the paradigm for hospital outbreak detection by leading with genomic surveillance of nosocomial pathogens

The current paradigm for hospital outbreak detection and investigation is based on methodology first developed over 150 years ago. Daily surveillance to detect patients positive for pathogens of particular importance for nosocomial infection is supported by epidemiological investigation to determine their relationship in time and place, and to identify any other factor that could link them. The antibiotic resistance pattern is commonly used as a surrogate for bacterial relatedness, although this lacks sensitivity and specificity. Typing may be used to define bacterial relatedness, although routine methods lack sufficient discriminatory power to distinguish relatedness beyond the level of bacterial clones. Ultimately, the identification of an outbreak remains a predominately subjective process reliant on the intuition of experienced infection control professionals. Here, we propose a redesign of hospital outbreak detection and investigation in which bacterial species associated with nosocomial transmission and infection undergo routine prospective whole-genome sequencing. Further investigation is based on the probability that isolates are associated with an outbreak, which is based on the degree of genetic relatedness between isolates. Evidence is provided that supports this model based on studies of MRSA (methicillin-resistant Staphylococcus aureus), together with the benefits of a 'Sequence First' approach. The feasibility of implementation is discussed, together with residual barriers that need to be overcome prior to implementation.

Genomics of Natural Populations of Staphylococcus aureus

Staphylococcus aureus is a major human pathogen and an important cause of livestock infections. The first S. aureus genomes to be published, 15 years ago, provided the first view of genome structure and gene content. Since then, thousands of genomes from a wide array of strains from different sources have been sequenced. Comparison of these sequences has resulted in broad insights into population structure, bacterial evolution, clone emergence and expansion, and the molecular basis of niche adaptation. Furthermore, this information is now being applied clinically in outbreak investigations to inform infection control measures and to determine appropriate treatment regimens. In this review, we summarize some of the broad insights into S. aureus biology gained from the analysis of genomes and discuss future directions and opportunities in this dynamic field of research.

Whole-genome sequencing reveals transmission of vancomycin-resistant Enterococcus faecium in a healthcare network

Background

Bacterial whole-genome sequencing (WGS) has the potential to identify reservoirs of multidrug-resistant organisms and transmission of these pathogens across healthcare networks. We used WGS to define transmission of vancomycin-resistant enterococci (VRE) within a long-term care facility (LTCF), and between this and an acute hospital in the United Kingdom (UK).

Methods

A longitudinal prospective observational study of faecal VRE carriage was conducted in a LTCF in Cambridge, UK. Stool samples were collected at recruitment, and then repeatedly until the end of the study period, discharge or death. Selective culture media were used to isolate VRE, which were subsequently sequenced and analysed. We also analysed the genomes of 45 Enterococcus faecium bloodstream isolates collected at Cambridge University Hospitals NHS Foundation Trust (CUH).

Results

Forty-five residents were recruited during a 6-month period in 2014, and 693 stools were collected at a frequency of at least 1 week apart. Fifty-one stool samples from 3/45 participants (7 %) were positive for vancomycin-resistant E. faecium. Two residents carried multiple VRE lineages, and one carried a single VRE lineage. Genome analyses based on single nucleotide polymorphisms (SNPs) in the core genome indicated that VRE carried by each of the three residents were unrelated. Participants had extensive contact with the local healthcare network. We found that VRE genomes from LTCF residents and hospital-associated bloodstream infection were interspersed throughout the phylogenetic tree, with several instances of closely related VRE strains from the two settings.

Conclusions

A proportion of LTCF residents are long-term carriers of VRE. Evidence for genetic relatedness between these and VRE associated with bloodstream infection in a nearby acute NHS Trust indicate a shared bacterial population.

Electronic supplementary material

The online version of this article (doi:10.1186/s13073-015-0259-7) contains supplementary material, which is available to authorized users.

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.

Whole-genome sequencing targets drug-resistant bacterial infections

During the past two decades, the technological progress of whole-genome sequencing (WGS) had changed the fields of Environmental Microbiology and Biotechnology, and, currently, is changing the underlying principles, approaches, and fundamentals of Public Health, Epidemiology, Health Economics, and national productivity. Today’s WGS technologies are able to compete with conventional techniques in cost, speed, accuracy, and resolution for day-to-day control of infectious diseases and outbreaks in clinical laboratories and in long-term epidemiological investigations. WGS gives rise to an exciting future direction for personalized Genomic Epidemiology. One of the most vital and growing public health problems is the emerging and re-emerging of multidrug-resistant (MDR) bacterial infections in the communities and healthcare settings, reinforced by a decline in antimicrobial drug discovery. In recent years, retrospective analysis provided by WGS has had a great impact on the identification and tracking of MDR microorganisms in hospitals and communities. The obtained genomic data are also important for developing novel easy-to-use diagnostic assays for clinics, as well as for antibiotic and therapeutic development at both the personal and population levels. At present, this technology has been successfully applied as an addendum to the real-time diagnostic methods currently used in clinical laboratories. However, the significance of WGS for public health may increase if: (a) unified and user-friendly bioinformatics toolsets for easy data interpretation and management are established, and (b) standards for data validation and verification are developed. Herein, we review the current and future impact of this technology on diagnosis, prevention, treatment, and control of MDR infectious bacteria in clinics and on the global scale.

Tackling Drug Resistant Infection Outbreaks of Global Pandemic Escherichia coli ST131 Using Evolutionary and Epidemiological Genomics

High-throughput molecular screening is required to investigate the origin and diffusion of antimicrobial resistance in pathogen outbreaks. The most frequent cause of human infection is Escherichia coli, which is dominated by sequence type 131 (ST131)-a set of rapidly radiating pandemic clones. The highly infectious clades of ST131 originated firstly by a mutation enhancing conjugation and adhesion. Secondly, single-nucleotide polymorphisms occurred enabling fluoroquinolone-resistance, which is near-fixed in all ST131. Thirdly, broader resistance through beta-lactamases has been gained and lost frequently, symptomatic of conflicting environmental selective effects. This flexible approach to gene exchange is worrying and supports the proposition that ST131 will develop an even wider range of plasmid and chromosomal elements promoting antimicrobial resistance. To stop ST131, deep genome sequencing is required to understand the origin, evolution and spread of antimicrobial resistance genes. Phylogenetic methods that decipher past events can predict future patterns of virulence and transmission based on genetic signatures of adaptation and gene exchange. Both the effect of partial antimicrobial exposure and cell dormancy caused by variation in gene expression may accelerate the development of resistance. High-throughput sequencing can decode measurable evolution of cell populations within patients associated with systems-wide changes in gene expression during treatments. A multi-faceted approach can enhance assessment of antimicrobial resistance in E. coli ST131 by examining transmission dynamics between hosts to achieve a goal of pre-empting resistance before it emerges by optimising antimicrobial treatment protocols.

Microbial sequencing to improve individual and population health

Recent advances in sequencing technologies are changing the face of infectious disease investigation and control. Personalized anti-infective therapies and surveillance of emergent pathogen outbreaks are just two examples of the potential benefits of merging the fields of genomics and infectious diseases.