Whole-genome Sequencing For Surveillance Research Articles

Real-time genomic epidemiologic investigation of a multispecies plasmid-associated hospital outbreak of NDM-5-producing Enterobacterales infections

New Delhi metallo-β-lactamase (NDM) is an emergent mechanism of carbapenem resistance associated with high mortality and limited treatment options. Because the blaNDM resistance gene is often carried on plasmids, traditional infection prevention and control (IP&C) surveillance methods and reactive whole genome sequencing (WGS) may not detect plasmid transfer in multispecies outbreaks. Initial outbreak detection of NDM-producing Enterobacterales identified at an acute care hospital occurred via traditional IP&C methods and was supplemented by real-time WGS surveillance performed weekly. To resolve NDM-encoding plasmids, we performed long-read sequencing and constructed hybrid assemblies. WGS data for suspected outbreaks was shared with the IP&C team for assessment and intervention. We observed a multispecies outbreak of NDM-5-producing Enterobacterales isolated from 15 patients between February 2021 and February 2023. The 19 clinical and surveillance isolates sequenced included 7 bacterial species encoding the same NDM-5 plasmid. WGS surveillance and epidemiologic investigation characterized 10 horizontal plasmid transfer events and 6 bacterial transmission events between patients in varying hospital units. Our investigation revealed a complex, multispecies outbreak of NDM involving multiple plasmid transfer and bacterial transmission events. We highlight the utility of combining traditional IP&C and prospective genomic methods in identifying and containing plasmid-associated outbreaks.

Whole-genome sequencing surveillance: Growing evidence for a future potential practice standard of infection prevention.

Whole-genome sequencing surveillance: Growing evidence for a future potential practice standard of infection prevention.

Population of invasive group A streptococci isolates from a German tertiary care center is dominated by the hypertoxigenic virulent M1UK genotype.

Hypertoxigenic Streptococcus pyogenes emm1 lineage M1UK has recently been associated with upsurges of invasive infections and scarlet fever in several countries, but whole-genome sequencing surveillance data of lineages circulating in Germany is lacking. In this study, we investigated recent iGAS isolates from our laboratory at a German tertiary care center for the presence of the M1UK lineage. Whole-genome sequencing was employed to characterize a collection of 47 consecutive non-copy isolates recovered from blood cultures (21) and tissue samples (26) in our laboratory between October 2022 and April 2023. M protein gene (emm) typing distinguished 14 different emm types, with emm1 (17) being the dominant type. Single-nucleotide polymorphism (SNP) analysis confirmed the presence of all 27 SNPs characteristic for the M1UK lineage in 14 of 17 emm1 isolates. This study has shown for the first time that M1UK is present in Germany and might constitute a driving force in the observed surge of GAS infections. This observation mirrors developments in the UK and other countries and underscores the importance of WGS surveillance to understand the epidemiology of GAS.

The Irish National SARS-CoV-2 Whole Genome Sequencing Surveillance Programme

Abstract Issue In response to the COVID-19 pandemic in Ireland, a national SARS-CoV-2 Whole Genome Sequencing (WGS) Surveillance Programme was set up in 2021 to track the molecular epidemiology of SARS-CoV-2 in Ireland to inform and enhance the urgent public health response to the COVID-19 pandemic. Description The Programme is a ‘hub and spoke’ model, led by the Health Protection Surveillance Centre with the National Virus Reference Laboratory (hub) and seven acute hospital laboratories (spokes), representing Ireland's six Regional Health Areas and Children's Health Ireland Hospitals. The two streams within the Programme's surveillance strategy are: 1. National surveillance of SARS-CoV-2 variants, including samples from GP sentinel sites and severe acute respiratory infection (SARI) surveillance, vaccine effectiveness studies, hospital in-patient, intensive care cases and deaths. 2. Targeted surveillance of risk groups e.g. outbreak cases, cases with unusual epidemiological/clinical characteristics. Results As of 30/03/2023, 103,258 COVID-19 cases (6% all notified cases in Ireland) have been sequenced since week 51, 2020. Data produced contribute to: public health policy in Ireland; local/national clinical and public health action; tracking variants nationally and variant shifts over time; the global community through reporting of WGS data to ECDC, WHO and global repository (GISAID). Lessons The hub and spoke model is an efficient and sustainable design for a laboratory public health programme. It is scalable, allowing addition of new spokes where needed. It ensures regional equity and builds capacity both nationally and regionally, increasing resilience and expertise throughout the country. Key messages • WGS will be key component of future epidemic/pandemic preparedness. • Programme successfully implements sustainable nationwide WGS surveillance and will expand to include other pathogens.

Environmental contamination of postmortem blood cultures detected by whole-genome sequencing surveillance.

Environmental contamination of postmortem blood cultures detected by whole-genome sequencing surveillance.

Economic and health impact modelling of a whole genome sequencing-led intervention strategy for bacterial healthcare-associated infections for England and for the USA.

Bacterial healthcare-associated infections (HAIs) are a substantial source of global morbidity and mortality. The estimated cost associated with HAIs ranges from $35 to $45 billion in the USA alone. The costs and accessibility of whole genome sequencing (WGS) of bacteria and the lack of sufficiently accurate, high-resolution, scalable and accessible analysis for strain identification are being addressed. Thus, it is timely to determine the economic viability and impact of routine diagnostic bacterial genomics. The aim of this study was to model the economic impact of a WGS surveillance system that proactively detects and directs interventions for nosocomial infections and outbreaks compared to the current standard of care, without WGS. Using a synthesis of published models, inputs from national statistics, and peer-reviewed articles, the economic impacts of conducting a WGS-led surveillance system addressing the 11 most common nosocomial pathogen groups in England and the USA were modelled. This was followed by a series of sensitivity analyses. England was used to establish the baseline model because of the greater availability of underpinning data, and this was then modified using USA-specific parameters where available. The model for the NHS in England shows bacterial HAIs currently cost the NHS around £3 billion. WGS-based surveillance delivery is predicted to cost £61.1 million associated with the prevention of 74 408 HAIs and 1257 deaths. The net cost saving was £478.3 million, of which £65.8 million were from directly incurred savings (antibiotics, consumables, etc.) and £412.5 million from opportunity cost savings due to re-allocation of hospital beds and healthcare professionals. The USA model indicates that the bacterial HAI care baseline costs are around $18.3 billion. WGS surveillance costs $169.2 million, and resulted in a net saving of ca.$3.2 billion, while preventing 169 260 HAIs and 4862 deaths. From a 'return on investment' perspective, the model predicts a return to the hospitals of £7.83 per £1 invested in diagnostic WGS in the UK, and US$18.74 per $1 in the USA. Sensitivity analyses show that substantial savings are retained when inputs to the model are varied within a wide range of upper and lower limits. Modelling a proactive WGS system addressing HAI pathogens shows significant improvement in morbidity and mortality while simultaneously achieving substantial savings to healthcare facilities that more than offset the cost of implementing diagnostic genomics surveillance.

TheiaEuk: a species-agnostic bioinformatics workflow for fungal genomic characterization.

The clinical incidence of antimicrobial-resistant fungal infections has dramatically increased in recent years. Certain fungal pathogens colonize various body cavities, leading to life-threatening bloodstream infections. However, the identification and characterization of fungal isolates in laboratories remain a significant diagnostic challenge in medicine and public health. Whole-genome sequencing provides an unbiased and uniform identification pipeline for fungal pathogens but most bioinformatic analysis pipelines focus on prokaryotic species. To this end, TheiaEuk_Illumina_PE_PHB (TheiaEuk) was designed to focus on genomic analysis specialized to fungal pathogens. TheiaEuk was designed using containerized components and written in the workflow description language (WDL) to facilitate deployment on the cloud-based open bioinformatics platform Terra. This species-agnostic workflow enables the analysis of fungal genomes without requiring coding, thereby reducing the entry barrier for laboratory scientists. To demonstrate the usefulness of this pipeline, an ongoing outbreak of C. auris in southern Nevada was investigated. We performed whole-genome sequence analysis of 752 new C. auris isolates from this outbreak. Furthermore, TheiaEuk was utilized to observe the accumulation of mutations in the FKS1 gene over the course of the outbreak, highlighting the utility of TheiaEuk as a monitor of emerging public health threats when combined with whole-genome sequencing surveillance of fungal pathogens. A primary result of this work is a curated fungal database containing 5,667 unique genomes representing 245 species. TheiaEuk also incorporates taxon-specific submodules for specific species, including clade-typing for Candida auris (C. auris). In addition, for several fungal species, it performs dynamic reference genome selection and variant calling, reporting mutations found in genes currently associated with antifungal resistance (FKS1, ERG11, FUR1). Using genome assemblies from the ATCC Mycology collection, the taxonomic identification module used by TheiaEuk correctly assigned genomes to the species level in 126/135 (93.3%) instances and to the genus level in 131/135 (97%) of instances, and provided zero false calls. Application of TheiaEuk to actual specimens obtained in the course of work at a local public health laboratory resulted in 13/15 (86.7%) correct calls at the species level, with 2/15 called at the genus level. It made zero incorrect calls. TheiaEuk accurately assessed clade type of Candida auris in 297/302 (98.3%) of instances. TheiaEuk demonstrated effectiveness in identifying fungal species from whole genome sequence. It further showed accuracy in both clade-typing of C. auris and in the identification of mutations known to associate with drug resistance in that organism.

Genomic diversity and epidemiological significance of non-typhoidal Salmonella found in retail food collected in Norfolk, UK.

Non-typhoidal Salmonella (NTS) is a major cause of bacterial gastroenteritis. Although many countries have implemented whole genome sequencing (WGS) of NTS, there is limited knowledge on NTS diversity on food and its contribution to human disease. In this study, the aim was to characterise the NTS genomes from retail foods in a particular region of the UK and assess the contribution to human NTS infections. Raw food samples were collected at retail in a repeated cross-sectional design in Norfolk, UK, including chicken (n=311), leafy green (n=311), pork (n=311), prawn (n=279) and salmon (n=157) samples. Up to eight presumptive NTS isolates per positive sample underwent WGS and were compared to publicly available NTS genomes from UK human cases. NTS was isolated from chicken (9.6 %), prawn (2.9 %) and pork (1.3 %) samples and included 14 serovars, of which Salmonella Infantis and Salmonella Enteritidis were the most common. The S. Enteritidis isolates were only isolated from imported chicken. No antimicrobial resistance determinants were found in prawn isolates, whilst 5.1 % of chicken and 0.64 % of pork samples contained multi-drug resistant NTS. The maximum number of pairwise core non-recombinant single nucleotide polymorphisms (SNPs) amongst isolates from the same sample was used to measure diversity and most samples had a median of two SNPs (range: 0-251). NTS isolates that were within five SNPs to clinical UK isolates belonged to specific serovars: S. Enteritidis and S. Infantis (chicken), and S. I 4,[5],12:i- (pork and chicken). Most NTS isolates that were closely related to human-derived isolates were obtained from imported chicken, but further epidemiological data are required to assess definitively the probable source of the human cases. Continued WGS surveillance of Salmonella on retail food involving multiple isolates from each sample is necessary to capture the diversity of Salmonella and determine the relative importance of different sources of human disease.

Real-time whole-genome sequencing surveillance for outbreak detection and intervention

Background: Detecting healthcare-associated transmission and outbreaks often relies on reactive whole-genome sequencing (WGS), which occurs after the suspected transmission has occurred. Additionally, reactive WGS frequently misidentifies transmission and misses transmission when it has occurred. We initiated weekly real-time WGS to detect bacterial transmission and direct infection prevention interventions. We describe our experience after 1 year of real-time WGS surveillance at the University of Pittsburgh Medical Center–Presbyterian Hospital, a large, tertiary-care facility. Methods: Weekly WGS surveillance was performed from November 1, 2021, to October 31, 2022. Cultured isolates of select bacterial pathogens from patients who were hospitalized for ≥3 days or had a recent healthcare exposure in the prior 30 days were collected and sequenced. Isolates that were ≤15 single-nucleotide polymorphisms (SNPs) were considered genetically related clusters except for Clostridioides difficile (≤2 SNPs). Genetically related clusters were investigated for epidemiological links and interventions to interrupt transmission were implemented at the discretion of the infection prevention team. We analyzed subsequent infections that occurred within an outbreak after an intervention was in place. Results: In total, 1,909 isolates were sequenced. Of 1,633 unique patient isolates clustered by sequence type, 74 clusters were identified comprising 210 (12.9%) patient isolates (Table 1). The median time from culture date to sequencing was 14 days (IQR, 5.25). The median cluster size was 2 (IQR, 1) (Table 2). Overall, 118 patient isolates (56.2%) had an epidemiological link to a prior isolate, indicating potential transmission. Of 74 clusters, 66 (89.2%) received infection prevention interventions after notification based upon epidemiological data. The infection prevention team performed 69 total interventions, which included unit education (n = 28), hand hygiene observations (n = 16), enhanced cleaning (n = 16), environmental cultures or removal of endoscope (n = 7), and enhanced microbiology surveillance (n = 2). The 59 subsequent infections after infection prevention notification included 17 (28.8%) with no clear epidemiological link, and 41 (69.5%) with an epidemiological link either to a new transmission route (n = 37) or the same route prior to infection prevention intervention (n = 4). Only 1 (1.7%) subsequent infection within a cluster occurred after an infection prevention intervention from the same potential route, which was a suspected unit-based transmission of vancomycin-resistant Enterococcus faecium. Conclusions: Real-time WGS was effective at detecting genetically related clusters, finding potential sources, and halting further transmission after interventions by the infection prevention team. Quick turnaround times from patient culture to sequencing and analysis were vital for successful WGS surveillance. Real-time WGS surveillance has the potential to substantially shift the infection prevention paradigm for outbreak detection.Disclosure: None

An overview of tuberculosis outbreaks reported in the years 2011–2020

BackgroundIn many countries tuberculosis (TB) remains a highly prevalent disease and a major contributor to infectious disease mortality. The fight against TB requires surveillance of the population of strains circulating worldwide and the analysis of the prevalence of certain strains in populations. Nowadays, whole genome sequencing (WGS) allows for accurate tracking of TB transmission. Currently, there is a lack of a comprehensive summary of the characteristics of TB outbreaks.MethodsWe systematically analyzed studies reporting TB outbreaks worldwide, monitored through WGS of Mycobacterium tuberculosis. We 1) mapped the reported outbreaks from 2011- 2020, 2) estimated the average size of the outbreaks, 3) indicated genetic lineages causing the outbreaks, and 4) determined drug-resistance patterns of M. tuberculosis strains involved in the outbreaks.ResultsMost data originated from Europe, Asia, and North America. We found that TB outbreaks were reported throughout the globe, on all continents, and in countries with both high and low incidences. The detected outbreaks contained a median of five M. tuberculosis isolates. Most strains causing the outbreaks belonged to lineage four, more rarely to lineage two. Reported outbreak isolates were often drug resistant.ConclusionsWe conclude that more WGS surveillance of M. tuberculosis outbreaks is needed. Globally standardized procedures might improve the control of M. tuberculosis infections.

Pyrazinamide-resistant Tuberculosis Obscured From Common Targeted Molecular Diagnostics

Here, we describe a clinical case of pyrazinamide-resistant (PZA-R) tuberculosis (TB) reported as PZA-susceptible (PZA-S) by common molecular diagnostics. Phenotypic susceptibility testing (pDST) indicated PZA-R TB. Targeted Sanger sequencing reported wild-type PncA, indicating PZA-S TB. Whole Genome Sequencing (WGS) by PacBio and IonTorrent both detected deletion of a large portion of pncA, indicating PZA-R. Importantly, both WGS methods showed deletion of part of the primer region targeted by Sanger sequencing. Repeating Sanger sequencing from a culture in presence of PZA returned no result, revealing that 1) two minority susceptible subpopulations had vanished, 2) the PZA-R majority subpopulation harboring the pncA deletion could not be amplified by Sanger primers, and was thus obscured by amplification process. This case demonstrates how a small susceptible subpopulation can entirely obscure majority resistant populations from targeted molecular diagnostics and falsely imply homogenous susceptibility, leading to incorrect diagnosis. To our knowledge, this is the first report of a minority susceptible subpopulation masking a majority resistant population, causing targeted molecular diagnostics to call false susceptibility. The consequence of such genomic events is not limited to PZA. This phenomenon can impact molecular diagnostics’ sensitivity whenever the resistance-conferring mutation is not fully within primer-targeted regions. This can be caused by structural changes of genomic context with phenotypic consequence as we report here, or by uncommon mechanisms of resistance. Such false susceptibility calls promote suboptimal treatment and spread of strains that challenge targeted molecular diagnostics. This motivates development of molecular diagnostics unreliant on primer conservation, and impels frequent WGS surveillance for variants that evade prevailing molecular diagnostics.

Sensitivity of National Healthcare Safety Network definitions to capture healthcare-associated transmission identified by whole-genome sequencing surveillance.

The National Healthcare Safety Network (NHSN) definitions are critical for standardizing healthcare-associated infection surveillance in US healthcare facilities. However, their use in accurately detecting healthcare-associated transmission (HAT) has not been measured. Using whole-genome sequencing surveillance data, we show that the NHSN has a sensitivity of 44.4% in detecting HAT.

Whole-genome sequencing of SARS-CoV-2 isolates from symptomatic and asymptomatic individuals in Tanzania.

Coronavirus Disease-2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) accounts for considerable morbidity and mortality globally. Paucity of SARS-CoV-2 genetic data from Tanzania challenges in-country tracking of the pandemic. We sequenced SARS-CoV-2 isolated in the country to determine circulating strains, mutations and phylogenies and finally enrich international genetic databases especially with sequences from Africa. This cross-sectional study utilized nasopharyngeal swabs of symptomatic and asymptomatic adults with positive polymerase chain reaction tests for COVID-19 from January to May 2021. Viral genomic libraries were prepared using ARTIC nCoV-2019 sequencing protocol version three. Whole-genome sequencing (WGS) was performed using Oxford Nanopore Technologies MinION device. In silico genomic data analysis was done on ARTIC pipeline version 1.2.1 using ARTIC nCoV-2019 bioinformatics protocol version 1.1.0. Twenty-nine (42%) out of 69 samples qualified for sequencing based on gel electrophoretic band intensity of multiplex PCR amplicons. Out of 29 isolates, 26 were variants of concern [Beta (n = 22); and Delta (n = 4)]. Other variants included Eta (n = 2) and B.1.530 (n = 1). We found combination of mutations (S: D80A, S: D215G, S: K417N, ORF3a: Q57H, E: P71L) in all Beta variants and absent in other lineages. The B.1.530 lineage carried mutations with very low cumulative global prevalence, these were nsp13:M233I, nsp14:S434G, ORF3a:A99S, S: T22I and S: N164H. The B.1.530 lineage clustered phylogenetically with isolates first reported in south-east Kenya, suggesting regional evolution of SARS-CoV-2. We provide evidence of existence of Beta, Delta, Eta variants and a locally evolving lineage (B.1.530) from samples collected in early 2021 in Tanzania. This work provides a model for ongoing WGS surveillance that will be required to inform on emerging and circulating SARS-CoV-2 diversity in Tanzania and East Africa.

Genomic surveillance reveals antibiotic resistance gene transmission via phage recombinases within sheep mastitis-associated Streptococcus uberis

BackgroundStreptococcus uberis is one of the main causative agents of ovine mastitis, however little is known about this global, environmental pathogen and its genomic mechanisms of disease. In this study, we performed genomic analysis on 46 S. uberis isolates collected from mastitis-infected sheep in Sardinia (Italy).ResultsGenomes were assigned into lineage clusters using PopPUNK, which found 27 distinct isolate clusters, indicating considerable genetic variability consistent with environmental isolates. Geographic trends were identified including regional linkage of several isolate clusters. Multi-locus Sequence Typing (MLST) performed poorly and provided no new insights.Genomes were then screened for antimicrobial resistance genes, which were compared to phenotypic resistance profiles. Isolates showed consistent phenotypic resistance to aminoglycosides with variable resistance to novobiocin and tetracycline. In general, identification of antimicrobial resistance genes did not correlate with phenotypic resistance profiles, indicating unknown genetic determinants. A multi-antimicrobial resistance cassette (aminoglycoside, lincosamide and streptogramin) was identified in the chromosome of three genomes, flanked by vestigial phage recombinases. This locus appears to have spread horizontally within discrete S. uberis populations within a 40 km radius (Sassari region).Genomes were screened for putative virulence factors, which identified 16 genes conserved between sheep and cow isolates, with no host-specific genes shared uniformly across all host-specific isolates.Pangenomic analysis was then performed to identify core genes which were putatively surface-exposed, for identification of potential vaccine targets. As all genomes encoded sortase, core genes were screened for the sortase cleavage motif. Of the 1445 core S. uberis genes, 64 were putative sortase substrates and were predominantly adhesins, permeases and peptidases, consistent with compounds found within ruminant milk such as xanthine, fibronectin and lactoferrin.ConclusionsThis study demonstrated the importance of whole genome sequencing for surveillance of S. uberis and tracking horizontal acquisition of antimicrobial resistance genes, as well as providing insight into genetic determinants of disease, which cannot be inferred from the MLST schemes. Future mastitis surveillance should be informed by genomic analysis.

Whole-genome sequencing enhances existing pathogen and antimicrobial-resistance surveillance schemes within a neonatal unit.

In some neonatal units, the screening of isolates for antimicrobial-resistant organisms is a matter of routine, with theoretical benefits including the prevention or early detection of outbreaks. This study sought to use whole-genome sequencing (WGS) retrospectively to characterize the genomic epidemiology of Gram-negative organisms obtained from a screening programme in a 32-bed unit providing intensive, high-dependency and special care at City Hospital, Birmingham, UK, identifying occult transmission events and clinically important antimicrobial-resistance (AMR) genes. WGS was performed for 155 isolates collected from rectal and umbilical screening swabs over a 2 month period from 44 individual neonates. Genomic epidemiological analysis showed possible transmission events involving Escherichia coli , Enterobacter cloacae , Klebsiella oxytoca and Klebsiella pneumoniae not detected by routine screening, with eight putative clusters involving different individuals identified. Within phylogenetic clusters, the relatedness of organisms – as determined by the abundance of SNPs – varied widely, indicating that a variety of transmission routes may be implicated. While clinically important AMR genes were not present in the putative transmission clusters, our observation of suspected interspecies horizontal transfer of bla CTX-M-15 within individuals highlights the potential for their spread between organisms as well as individuals in this environment, with implications for surveillance. Our data show that WGS may reveal occult Gram-negative transmission events, demonstrating the potential of sequencing-based surveillance systems for nosocomial pathogens. Challenges remain in understanding how to utilize WGS surveillance to maximum effect in real-world settings.

Research and implementation of a whole-genome sequencing surveillance system for outbreak detection

Background: Traditional infection prevention (IP) methods for outbreak detection often rely on geotemporal clustering confined to single locations. We recently developed the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), which combines whole-genome sequencing (WGS) surveillance and machine learning of the electronic health record (EHR). Our retrospective research findings show potential transmissions averted and cost savings using EDS-HAT in real time. Here, we describe the process and initial findings from EDS-HAT real-time implementation. Methods: Real-time whole-genome sequencing surveillance began on November 1, 2021. Patient cultures positive for select bacterial pathogens who were hospitalized for ≥3 days or had a recent healthcare exposure in the prior 30-days were collected. Isolates were deemed genetically related if ≤15 single-nucleotide polymorphisms (SNPs) were identified for all organisms except Clostridioides difficile (≤2 SNPs). Clusters were manually investigated by both research and IP teams, and interventions were performed by the IP team. Data on collection, analysis, notification, and intervention dates were gathered. Results: As of January 11, 2022, 413 isolates had undergone whole-genome sequencing. Among them, 18 unique patient isolates were genetically related to ≥1 other isolate, comprising 7 clusters (range, 2–6 patients). Notable findings include a Pseudomonas aeruginosa cluster possibly related to a shared bronchoscope, a pseudo-outbreak of Serratia marcescens related to autopsy blood culture practice, and a cluster of vancomycin-resistant Enterococcus faecium on a shared transplant unit. Only 1 cluster of 2 isolates of Klebsiella pneumoniae had no known possible transmission routes. The median turnaround time from patient’s culture date to IP notification was 19 days (range, 13–28), with noted delays over the winter holiday. Concusions: Real-time WGS can identify small clusters including potentially interruptible transmission routes. Rapid turnaround time, coordination between clinical and genomic laboratories, and a robust IP team are key factors in implementing a WGS surveillance program. Real-time WGS surveillance has the potential to reduce costs for hospitals, improve patient safety, and save lives.Funding: NoneDisclosures: None

WHO Critical Priority Escherichia coli as One Health Challenge for a Post-Pandemic Scenario: Genomic Surveillance and Analysis of Current Trends in Brazil.

ABSTRACTThe dissemination of carbapenem-resistant and third generation cephalosporin-resistant pathogens is a critical issue that is no longer restricted to hospital settings. The rapid spread of critical priority pathogens in Brazil is notably worrying, considering its continental dimension, the diversity of international trade, livestock production, and human travel. We conducted a nationwide genomic investigation under a One Health perspective that included Escherichia coli strains isolated from humans and nonhuman sources, over 45 years (1974–2019). One hundred sixty-seven genomes were analyzed extracting clinically relevant information (i.e., resistome, virulome, mobilome, sequence types [STs], and phylogenomic). The endemic status of extended-spectrum β-lactamase (ESBL)-positive strains carrying a wide diversity of blaCTX-M variants, and the growing number of colistin-resistant isolates carrying mcr-type genes was associated with the successful expansion of international ST10, ST38, ST115, ST131, ST354, ST410, ST648, ST517, and ST711 clones; phylogenetically related and shared between human and nonhuman hosts, and polluted aquatic environments. Otherwise, carbapenem-resistant ST48, ST90, ST155, ST167, ST224, ST349, ST457, ST648, ST707, ST744, ST774, and ST2509 clones from human host harbored blaKPC-2 and blaNDM-1 genes. A broad resistome to other clinically relevant antibiotics, hazardous heavy metals, disinfectants, and pesticides was further predicted. Wide virulome associated with invasion/adherence, exotoxin and siderophore production was related to phylogroup B2. The convergence of wide resistome and virulome has contributed to the persistence and rapid spread of international high-risk clones of critical priority E. coli at the human-animal-environmental interface, which must be considered a One Health challenge for a post-pandemic scenario.IMPORTANCE A One Health approach for antimicrobial resistance must integrate whole-genome sequencing surveillance data of critical priority pathogens from human, animal and environmental sources to track hot spots and routes of transmission and developing effective prevention and control strategies. As part of the Grand Challenges Explorations: New Approaches to Characterize the Global Burden of Antimicrobial Resistance Program, we present genomic data of WHO critical priority carbapenemase-resistant, ESBL-producing, and/or colistin-resistant Escherichia coli strains isolated from humans and nonhuman sources in Brazil, a country with continental proportions and high levels of antimicrobial resistance. The present study provided evidence of epidemiological and clinical interest, highlighting that the convergence of wide virulome and resistome has contributed to the persistence and rapid spread of international high-risk clones of E. coli at the human-animal-environmental interface, which must be considered a One Health threat that requires coordinated actions to reduce its incidence in humans and nonhuman hosts.

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

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

Whole-Genome Sequencing Surveillance and Machine Learning of the Electronic Health Record for Enhanced Healthcare Outbreak Detection.

Most hospitals use traditional infection prevention (IP) methods for outbreak detection. We developed the Enhanced Detection System for Healthcare-Associated Transmission (EDS-HAT), which combines whole-genome sequencing (WGS) surveillance and machine learning (ML) of the electronic health record (EHR) to identify undetected outbreaks and the responsible transmission routes, respectively. We performed WGS surveillance of healthcare-associated bacterial pathogens from November 2016 to November 2018. EHR ML was used to identify the transmission routes for WGS-detected outbreaks, which were investigated by an IP expert. Potential infections prevented were estimated and compared with traditional IP practice during the same period. Of 3165 isolates, there were 2752 unique patient isolates in 99 clusters involving 297 (10.8%) patient isolates identified by WGS; clusters ranged from 2-14 patients. At least 1 transmission route was detected for 65.7% of clusters. During the same time, traditional IP investigation prompted WGS for 15 suspected outbreaks involving 133 patients, for which transmission events were identified for 5 (3.8%). If EDS-HAT had been running in real time, 25-63 transmissions could have been prevented. EDS-HAT was found to be cost-saving and more effective than traditional IP practice, with overall savings of $192 408-$692 532. EDS-HAT detected multiple outbreaks not identified using traditional IP methods, correctly identified the transmission routes for most outbreaks, and would save the hospital substantial costs. Traditional IP practice misidentified outbreaks for which transmission did not occur. WGS surveillance combined with EHR ML has the potential to save costs and enhance patient safety.

Whole genome sequencing reveals great diversity of Vibrio spp in prawns at retail.

Consumption of prawns as a protein source has been on the rise worldwide with seafood identified as the predominant attributable source of human vibriosis. However, surveillance of non-cholera Vibrio is limited both in public health and in food. Using a population- and market share-weighted study design, 211 prawn samples were collected and cultured for Vibrio spp. Contamination was detected in 46 % of samples, and multiple diverse Vibrio isolates were obtained from 34 % of positive samples. Whole genome sequencing (WGS) and phylogenetic analysis illustrated a comprehensive view of Vibrio species diversity in prawns available at retail, with no known pathogenicity markers identified in Vibrio parahaemolyticus and V. cholerae . Antimicrobial resistance genes were found in 77 % of isolates, and 12 % carried genes conferring resistance to three or more drug classes. Resistance genes were found predominantly in V. parahaemolyticus , though multiple resistance genes were also identified in V. cholerae and V. vulnificus . This study highlights the large diversity in Vibrio derived from prawns at retail, even within a single sample. Although there was little evidence in this study that prawns are a major source of vibriosis in the UK, surveillance of non-cholera Vibrio is very limited. This study illustrates the value of expanding WGS surveillance efforts of non-cholera Vibrios in the food chain to identify critical control points for food safety through the production system and to determine the full extent of the public health impact.