Surveillance-embedded genomic outbreak resolution of methicillin-susceptible Staphylococcus aureus in a neonatal intensive care unit

The mobilome of Staphylococcus aureus from wild ungulates reveals epidemiological links at the animal-human interface

Staphylococcus aureus thrives at animal-human-environment interfaces. A large-scale work from our group indicated that antimicrobial resistance (AMR) in commensal S. aureus strains from wild ungulates is associated with agricultural land cover and livestock farming, raising the hypothesis that AMR genes in wildlife strains may originate from different hosts, namely via exchange of mobile genetic elements (MGE). In this work, we generate the largest available dataset of S. aureus draft genomes from wild ungulates in Portugal and explore their mobilome, which can determine important traits such as AMR, virulence, and host specificity, to understand MGE exchange. Core genome multi-locus sequence typing based on 98 newly generated draft genomes and 101 publicly available genomes from Portugal demonstrated that the genomic relatedness of S. aureus from wild ungulates assigned to livestock-associated sequence types (ST) is greater compared to wild ungulate isolates assigned to human-associated STs. Screening of host specificity determinants disclosed the unexpected presence in wildlife of the immune evasion cluster encoded in φSa3 prophage, described as a human-specific virulence determinant. Additionally, two plasmids, pAVX and pETB, previously associated with avian species and humans, respectively, and the Tn553 transposon were detected. Both pETB and Tn553 encode penicillin resistance through blaZ. Pangenome analysis of wild ungulate isolates shows a core genome fraction of 2133 genes, with isolates assigned to ST72 and ST3224 being distinguished from the remaining by MGEs, although there is no reported role of these in adaptation to wildlife. AMR related gene clusters found in the shell genome are directly linked to resistance against penicillin, macrolides, fosfomycin, and aminoglycosides, and they represent mobile ARGs. Altogether, our findings support epidemiological interactions of human and non-human hosts at interfaces, with MGE exchange, including AMR determinants, associated with putative indirect movements of S. aureus among human and wildlife hosts that might be bridged by livestock.

Risk factors for methicillin-resistant Staphylococcus aureus colonization in a level-IV neonatal intensive care unit: a retrospective study

Objective

To identify risk factors associated with methicillin-resistant Staphylococcus aureus (MRSA) colonization in neonatal patients during an MRSA outbreak to minimize future outbreaks.

Design

Retrospective case-control study.

Setting

Level-IV neonatal intensive care unit (NICU) at Copenhagen University Hospital, Rigshospitalet, Denmark.

Patients

Neonates with either MRSA or methicillin-susceptible Staphylococcus aureus (MSSA).

Methods

Methicillin-resistant Staphylococcus aureus-positive neonates were matched with those colonized or infected with MSSA in a 1:1 ratio. The control group was selected from clinical samples, whereas MRSA-positive neonates were identified from clinical samples or from screening. A total of 140 characteristics were investigated to identify risk factors associated with MRSA acquisition. The characteristics were categorized into three categories: patient, unit, and microbiological characteristics.

Results

Out of 1,102 neonates screened for MRSA, between December 2019 and January 2022, 33 were MRSA positive. They were all colonized with an MRSA outbreak clone (spa type t127) and were included in this study. Four patients (12%) had severe infection. Admission due to respiratory diseases, need for intubation, need for peripheral venous catheters, admission to shared rooms with shared toilets and bath facilities in the aisles, and need for readmission were all correlated with later MRSA colonization (P < 0.05).

Conclusion

We identified clinically relevant diseases, procedures, and facilities that predispose patients to potentially life-threatening MRSA infections. A specific MRSA reservoir remains unidentified; however, these findings have contributed to crucial changes in our NICU to reduce the number of MRSA infections and future outbreaks.

Genome-based typing reveals rare events of patient contamination with Pseudomonas aeruginosa from other patients and sink traps in a medical intensive care unit

AIM

We used genome-based typing data with the aim of identifying the routes of acquisition of Pseudomonas aeruginosa by patients hospitalized in a medical intensive care unit (MICU) over a long period in a non-epidemic context.

METHODS

This monocentric prospective study took place over 10 months in 2019 in a 15-bed MICU that applies standard precautions of hygiene. Lockable sink traps installed at all water points of use were bleach disinfected twice a week. We sampled all sink traps weekly to collect 404 P. aeruginosa environmental isolates and collected all P. aeruginosa isolates (N = 115) colonizing or infecting patients (N = 65). All isolates had their phenotypic resistance profile determined and their genome sequenced, from which we identified resistance determinants and assessed the population structure of the collection at the nucleotide level to identify events of P. aeruginosa transmission.

FINDINGS

All sink traps were positive for P. aeruginosa, each sink trap being colonized for several months by one or more clones. The combination of genomic and spatiotemporal data identified one potential event of P. aeruginosa transmission from a sink trap to a patient (1/65, 1.5%) and six events of patient cross-transmission, leading to the contamination of five patients (5/65, 7.7%). All transmitted isolates were fully susceptible to β-lactams and aminoglycosides.

CONCLUSIONS

Genome-based typing revealed the contamination of patients by P. aeruginosa originating from sink traps to be infrequent (1.5%) in an MICU with sink trap-bleaching measures, and that only 7.7% of the patients acquired P. aeruginosa originating from another patient.

Comparison of fast Fourier transform infrared spectroscopy biotyping with whole genome sequencing-based genotyping in common nosocomial pathogens

Early detection of bacterial transmission and outbreaks in hospitals is important because nosocomial infections can result in health complications and longer hospitalization. Current practice to detect outbreaks uses genotyping methods amplified fragment length polymorphism (AFLP) and whole genome sequencing (WGS), which are not suitable methods for real-time transmission screening of both susceptible and resistant bacteria. The aim was to assess the typing technique Fourier transform infrared (FTIR) spectroscopy as real-time screening method to discriminate large amounts of susceptible and resistant bacteria at strain level when there is no evident outbreak in comparison with the WGS reference. Isolates of past hospital outbreak strains of Acinetobacter baumannii/calcoaceticus complex (n = 25), Escherichia coli (n = 31), Enterococcus faecium (n = 22), Staphylococcus aureus (n = 37) and Pseudomonas aeruginosa (n = 30) were used for validation of FTIR. Subsequently, Enterococcus faecalis (n = 106) and Enterococcus faecium (n = 104) isolates from weekly routine screening samples when no potential outbreak was present were analysed. FTIR showed reproducibility and congruence of cluster composition with WGS for A. baumannii/calcoaceticus complex and E. faecium outbreak isolates. The FTIR results of E. faecalis and E. faecium isolates from routine samples showed reproducibility, but the congruence of cluster composition with WGS was low. For A. baumannii/calcoaceticus complex and E. faecium outbreak isolates, FTIR appears to be a discriminatory typing tool. However, our study shows the discriminatory power is too low to screen real-time for transmission of E. faecium and E. faecalis at patient wards based on isolates acquired in routine surveillance cultures when there is no clear suspicion of an ongoing outbreak.

Whole-genome sequencing surveillance and machine learning for healthcare outbreak detection and investigation: A systematic review and summary

BACKGROUND

Whole-genome sequencing (WGS) has traditionally been used in infection prevention to confirm or refute the presence of an outbreak after it has occurred. Due to decreasing costs of WGS, an increasing number of institutions have been utilizing WGS-based surveillance. Additionally, machine learning or statistical modeling to supplement infection prevention practice have also been used. We systematically reviewed the use of WGS surveillance and machine learning to detect and investigate outbreaks in healthcare settings.

METHODS

We performed a PubMed search using separate terms for WGS surveillance and/or machine-learning technologies for infection prevention through March 15, 2021.

RESULTS

Of 767 studies returned using the WGS search terms, 42 articles were included for review. Only 2 studies (4.8%) were performed in real time, and 39 (92.9%) studied only 1 pathogen. Nearly all studies (n = 41, 97.6%) found genetic relatedness between some isolates collected. Across all studies, 525 outbreaks were detected among 2,837 related isolates (average, 5.4 isolates per outbreak). Also, 35 studies (83.3%) only utilized geotemporal clustering to identify outbreak transmission routes. Of 21 studies identified using the machine-learning search terms, 4 were included for review. In each study, machine learning aided outbreak investigations by complementing methods to gather epidemiologic data and automating identification of transmission pathways.

CONCLUSIONS

WGS surveillance is an emerging method that can enhance outbreak detection. Machine learning has the potential to identify novel routes of pathogen transmission. Broader incorporation of WGS surveillance into infection prevention practice has the potential to transform the detection and control of healthcare outbreaks.

NGSocomial Infections: High-Resolution Views of Hospital-Acquired Infections Through Genomic Epidemiology

Hospital outbreak investigations are high-stakes epidemiology. Contacts between staff and patients are numerous; environmental and community exposures are plentiful; and patients are highly vulnerable. Having the best data is paramount to understanding an outbreak in order to stop ongoing transmission and prevent future outbreaks. In the past 5 years, the high-resolution view of transmission offered by analyzing pathogen whole-genome sequencing (WGS) is increasingly part of hospital outbreak investigations. Concerns over speed and actionability, assay validation, liability, cost, and payment models lead to further opportunities for work in this area. Now accelerated by funding for COVID-19, the use of genomics in hospital outbreak investigations has firmly moved from the academic literature to more quotidian operations, with associated concerns involving regulatory affairs, data integration, and clinical interpretation. This review details past uses of WGS data in hospital-acquired infection outbreaks as well as future opportunities to increase its utility and growth in hospital infection prevention.

Whole Genome Sequencing Provides an Added Value to the Investigation of Staphylococcal Food Poisoning Outbreaks

Through staphylococcal enterotoxin (SE) production, Staphylococcus aureus is a common cause of food poisoning. Detection of staphylococcal food poisoning (SFP) is mostly performed using immunoassays, which, however, only detect five of 27 SEs described to date. Polymerase chain reactions are, therefore, frequently used in complement to identify a bigger arsenal of SE at the gene level (se) but are labor-intensive. Complete se profiling of isolates from different sources, i.e., food and human cases, is, however, important to provide an indication of their potential link within foodborne outbreak investigation. In addition to complete se gene profiling, relatedness between isolates is determined with more certainty using pulsed-field gel electrophoresis, Staphylococcus protein A gene typing and other methods, but these are shown to lack resolution. We evaluated how whole genome sequencing (WGS) can offer a solution to these shortcomings. By WGS analysis of a selection of S. aureus isolates, including some belonging to a confirmed foodborne outbreak, its added value as the ultimate multiplexing method was demonstrated. In contrast to PCR-based se gene detection for which primers are sometimes shown to be non-specific, WGS enabled complete se gene profiling with high performance, provided that a database containing reference sequences for all se genes was constructed and employed. The custom compiled database and applied parameters were made publicly available in an online user-friendly interface. As an all-in-one approach with high resolution, WGS additionally allowed inferring correct isolate relationships. The different DNA extraction kits that were tested affected neither se gene profiling nor relatedness determination, which is interesting for data sharing during SFP outbreak investigation. Although confirming the production of enterotoxins remains important for SFP investigation, we delivered a proof-of-concept that WGS is a valid alternative and/or complementary tool for outbreak investigation.

Surveillance for Colonization, Transmission, and Infection With Methicillin-Susceptible Staphylococcus aureus in a Neonatal Intensive Care Unit

IMPORTANCE

Staphylococcus aureus is one of the leading causes of infections in neonatal intensive care units (NICUs). Most studies in this patient group focus on methicillin-resistant S aureus or the outbreak setting, whereas data for methicillin-susceptible S aureus are limited.

OBJECTIVES

To identify risk factors for S aureus colonization and infections in hospitalized newborns and to investigate S aureus transmission and its dynamics in a nonoutbreak setting.

DESIGN, SETTING, AND PARTICIPANTS

This monocentric cohort study in a tertiary NICU in Heidelberg, Germany, enrolled all hospitalized neonates (n = 590) with at least 1 nasal screening swab positive for S aureus. Data were collected from January 1, 2018, to December 31, 2019.

EXPOSURES

Weekly screening for S aureus colonization was performed for all newborns until discharge.

MAIN OUTCOMES AND MEASURES

The primary end point was any S aureus infection until hospital discharge. Transmission of S aureus and performance of routine typing to detect transmissions were defined as the secondary outcomes of the study.

RESULTS

In total, 590 newborns were enrolled (276 [46.8%] female and 314 [53.2%] male; 220 [37.3%] with birthweight <1500 g; 477 [80.8%] preterm; 449 [76.1%] singletons; 419 [71.5%] delivered via cesarean section). The median length of stay was 26 (range, 10-62) days. Overall, 135 infants (22.9%) were colonized by S aureus at some time during their hospital stay. The median time to first detection was 17 (interquartile range, 11-37) days. The overall incidence of S aureus infection was 1.7% (10 of 590). Low birth weight (<1500 g [odds ratio, 9.3; 95% CI, 5.9-14.6; P < .001]) and longer hospital stay (odds ratio, 2.3; 95% CI, 1.9-2.7; P < .001) were associated with colonization. Nasal carriage was significantly associated with S aureus infection (odds ratio, 8.2; 95% CI, 2.1-32.3; P = .002). A total of 123 of 135 colonization isolates were sequenced. All recoverable infection isolates (4 of 7) of newborns with colonization were genetically identical to the colonizing isolate. Whole-genome sequencing indicated 23 potential transmission clusters.

CONCLUSIONS AND RELEVANCE

The findings of this cohort study suggest that nasal colonization is a relevant risk factor for S aureus infection in a nonoutbreak NICU setting. In colonized newborns, infection and colonization isolates were genetically identical, suggesting that eradication of colonization may be a useful measure to prevent infection. Further investigations are necessary to validate and assess the generalizability of our findings.

Centre-specific bacterial pathogen typing affects infection-control decision making

Whole-genome sequencing is becoming the de facto standard for bacterial outbreak surveillance and infection prevention. This is accompanied by a variety of bioinformatic tools and needs bioinformatics expertise for implementation. However, little is known about the concordance of reported outbreaks when using different bioinformatic workflows. In this multi-centre proficiency testing among 13 major Dutch healthcare-affiliated centres, bacterial whole-genome outbreak analysis was assessed. Centres who participated obtained two randomized bacterial datasets of Illumina sequences, a Klebsiella pneumoniae and a Vancomycin-resistant Enterococcus faecium, and were asked to apply their bioinformatic workflows. Centres reported back on antimicrobial resistance, multi-locus sequence typing (MLST), and outbreak clusters. The reported clusters were analysed using a method to compare landscapes of phylogenetic trees and calculating Kendall–Colijn distances. Furthermore, fasta files were analysed by state-of-the-art single nucleotide polymorphism (SNP) analysis to mitigate the differences introduced by each centre and determine standardized SNP cut-offs. Thirteen centres participated in this study. The reported outbreak clusters revealed discrepancies between centres, even when almost identical bioinformatic workflows were used. Due to stringent filtering, some centres failed to detect extended-spectrum beta-lactamase genes and MLST loci. Applying a standardized method to determine outbreak clusters on the reported de novo assemblies, did not result in uniformity of outbreak-cluster composition among centres.

Techniques in bacterial strain typing: past, present, and future

PURPOSE OF REVIEW

The advancement of molecular techniques such as whole-genome sequencing (WGS) has revolutionized the field of bacterial strain typing, with important implications for epidemiological surveillance and outbreak investigations. This review summarizes state-of-the-art techniques in strain typing and examines barriers faced by clinical and public health laboratories in implementing these new methodologies.

RECENT FINDINGS

WGS-based methodologies are on track to become the new 'gold standards' in bacterial strain typing, replacing traditional methods like pulsed-field gel electrophoresis and multilocus sequence typing. These new techniques have an improved ability to identify genetic relationships among organisms of interest. Further, advances in long-read sequencing approaches will likely provide a highly discriminatory tool to perform pangenome analyses and characterize relevant accessory genome elements, including mobile genetic elements carrying antibiotic resistance determinants in real time. Barriers to widespread integration of these approaches include a lack of standardized workflows and technical training.

SUMMARY

Genomic bacterial strain typing has facilitated a paradigm shift in clinical and molecular epidemiology. The increased resolution that these new techniques provide, along with epidemiological data, will facilitate the rapid identification of transmission routes with high confidence, leading to timely and effective deployment of infection control and public health interventions in outbreak settings.

A whole-genome sequencing study of an X-family tuberculosis outbreak focus on transmission chain along 25 years

Lineage 4/X-family of Mycobacterium tuberculosis is not very notorious, except for the CDC1551 strain. One strain of this family, named Ara50, caused one of the largest tuberculosis outbreaks of the Aragon region, Spain, during the 1990s and remained until 2018. These X-strains are characterised by high transmissibility and by carrying a low copy number of IS6110 in their genomes. Epidemiological data of the 61 patients consisted of inmates, HIV seropositives, intravenous drug users and the homeless. The application of whole-genome sequencing (WGS) to 36 out of 61 isolates, selected by IS6110-RFLP, allowed to confirm 32 as recent transmissions. We found 10 SNPs in genes considered as virulence factors, five of them specific of this strain. WGS identified three sub-clusters (CLSs). The largest one, sub-CLS 1, included 10 cases. Seven of them shared a SNP in the mce3C gene, considered a virulence factor gene. Sub-CLS 2 involved familiar cases, and no link was known for sub-CLS 3. Finally, the strain showed efficacy in latency as a confirmed epidemiological link was established between two cases, with 6 years of distance in their diagnosis. This outbreak study combined epidemiological and molecular analyses in order to elucidate tuberculosis transmission.

Surveillance-embedded genomic outbreak resolution of methicillin-susceptible Staphylococcus aureus in a neonatal intensive care unit

We observed an increase in methicillin-susceptible Staphylococcus aureus (MSSA) infections at a Dutch neonatal intensive care unit. Weekly neonatal MSSA carriage surveillance and cross-sectional screenings of health care workers (HCWs) were available for outbreak tracing. Traditional clustering of MSSA isolates by spa typing and Multiple-Locus Variable number tandem repeat Analysis (MLVA) suggested that nosocomial transmission had contributed to the infections. We investigated whether whole-genome sequencing (WGS) of MSSA surveillance would provide additional evidence for transmission. MSSA isolates from neonatal infections, carriage surveillance, and HCWs were subjected to WGS and bioinformatic analysis for identification and localization of high-quality single nucleotide polymorphisms, and in-depth analysis of subsets of isolates. By measuring the genetic diversity in background surveillance, we defined transmission-level relatedness and identified isolates that had been unjustly assigned to clusters based on MLVA, while spa typing was concordant but of insufficient resolution. Detailing particular subsets of isolates provided evidence that HCWs were involved in multiple outbreaks, yet it alleviated concerns about one particular HCW. The improved resolution and accuracy of genomic outbreak analyses substantially altered the view on outbreaks, along with apposite measures. Therefore, inclusion of the circulating background population has the potential to overcome current issues in genomic outbreak inference.