Sequence analyses of pathogen genomes facilitate the tracking of disease outbreaks and allow relationships between strains to be reconstructed and virulence factors to be identified. However, these ...methods are generally used after an outbreak has happened. Here, we show that support vector machine analysis of bovine E. coli O157 isolate sequences can be applied to predict their zoonotic potential, identifying cattle strains more likely to be a serious threat to human health. Notably, only a minor subset (less than 10%) of bovine E. coli O157 isolates analyzed in our datasets were predicted to have the potential to cause human disease; this is despite the fact that the majority are within previously defined pathogenic lineages I or I/II and encode key virulence factors. The predictive capacity was retained when tested across datasets. The major differences between human and bovine E. coli O157 isolates were due to the relative abundances of hundreds of predicted prophage proteins. This finding has profound implications for public health management of disease because interventions in cattle, such a vaccination, can be targeted at herds carrying strains of high zoonotic potential. Machine-learning approaches should be applied broadly to further our understanding of pathogen biology.
Shiga toxin-producing Escherichia coli (STEC) are zoonotic and transmission to humans occurs via contaminated food or contact with infected animals. In this study, WGS data were used to predict ...antimicrobial resistance (AMR) in STEC from symptomatic human cases to assess the extent of transmission of antibiotic-resistant E. coli from animals to humans.
WGS data from 430 isolates of STEC were mapped to genes known to be associated with phenotypic AMR. Susceptibility testing was performed by a breakpoint method on all viable isolates exhibiting resistance to at least one antimicrobial.
327/396 (82.6%) of STEC O157 and 22/34 (64.7%) of STEC O26 lacked identifiable resistance genes and were predicted to be fully susceptible to 11 diverse classes of antimicrobials. For the remaining 81 isolates, 74 were phenotypically tested and there was concordance between WGS-predicted resistance and expression of phenotypic resistance. The most common resistance profile was ampicillin, streptomycin, trimethoprim/sulphonamide and tetracycline occurring in 25 (5.8%) isolates. Resistance to other antimicrobials, including resistance to chloramphenicol (2.1%), resistance to azithromycin (0.2%) and reduced susceptibility to ciprofloxacin (2.6%), was less frequent. Three isolates were identified as ESBL producers.
β-Lactams, trimethoprim/sulphonamides and tetracyclines account for the majority of therapeutic antimicrobials sold for veterinary use and this may be a risk factor for the presence of AMR in domestically acquired human clinical isolates of STEC. Isolates that were resistant to ampicillin, streptomycin, sulphonamide, tetracycline and azithromycin and had reduced susceptibility to ciprofloxacin were associated with cases who reported recent travel abroad.
serovar Enteritidis is one of the most frequent causes of Salmonellosis globally and is commonly transmitted from animals to humans by the consumption of contaminated foodstuffs. In the UK and many ...other countries in the Global North, a significant proportion of cases are caused by the consumption of imported food products or contracted during foreign travel, therefore, making the rapid identification of the geographical source of new infections a requirement for robust public health outbreak investigations. Herein, we detail the development and application of a hierarchical machine learning model to rapidly identify and trace the geographical source of
Enteritidis infections from whole genome sequencing data. 2313
Enteritidis genomes, collected by the UKHSA between 2014-2019, were used to train a 'local classifier per node' hierarchical classifier to attribute isolates to four continents, 11 sub-regions, and 38 countries (53 classes). The highest classification accuracy was achieved at the continental level followed by the sub-regional and country levels (macro F1: 0.954, 0.718, 0.661, respectively). A number of countries commonly visited by UK travelers were predicted with high accuracy (hF1: >0.9). Longitudinal analysis and validation with publicly accessible international samples indicated that predictions were robust to prospective external datasets. The hierarchical machine learning framework provided granular geographical source prediction directly from sequencing reads in <4 min per sample, facilitating rapid outbreak resolution and real-time genomic epidemiology. The results suggest additional application to a broader range of pathogens and other geographically structured problems, such as antimicrobial resistance prediction, is warranted.
Abstract
Objectives
To compare and evaluate phenotypic and genotypic methods for the detection of antimicrobial resistance (AMR) in Campylobacter jejuni and Campylobacter coli in England and Wales.
...Methods
WGS data from 528 isolates of Campylobacter spp. (452 C. jejuni and 76 C. coli) from human (494), food (21) and environmental (2) sources, collected between January 2015 and December 2016, and from the PHE culture collection (11) were mapped to genes known to be associated with phenotypic resistance to antimicrobials in the genus. Phenotypic antibiotic susceptibility (erythromycin, ciprofloxacin, tetracycline, gentamicin and streptomycin) testing using an in-agar dilution method was performed on all isolates.
Results
Concordance between phenotypic resistance and the presence of corresponding AMR determinants was 97.5% (515/528 isolates). Only 13 out of 528 isolates (10 C. jejuni and 3 C. coli) had discordant interpretations for at least one of the five antibiotics tested, equating to a total of 15 (0.6%) discrepancies out of 2640 isolate/antimicrobial combinations. Seven discrepant results were genotypically resistant but phenotypically susceptible (major errors) and eight discrepant results were genotypically susceptible but phenotypically resistant (very major errors).
Conclusions
The use of this bioinformatics approach for predicting AMR from WGS data for routine public health surveillance is a reliable method for real-time monitoring of changing AMR patterns in isolates of C. jejuni and C. coli.
Following a large outbreak of foodborne gastrointestinal (GI) disease, a multiplex PCR approach was used retrospectively to investigate faecal specimens from 88 of the 413 reported cases. Gene ...targets from a range of bacterial GI pathogens were detected, including Salmonella species, Shigella species and Shiga toxin-producing Escherichia coli, with the majority (75%) of faecal specimens being PCR positive for aggR associated with the Enteroaggregative E. coli (EAEC) group. The 20 isolates of EAEC recovered from the outbreak specimens exhibited a range of serotypes, the most frequent being O104:H4 and O131:H27. None of the EAEC isolates had the Shiga toxin (stx) genes. Multilocus sequence typing and single nucleotide polymorphism analysis of the core genome confirmed the diverse phylogeny of the strains. The analysis also revealed a close phylogenetic relationship between the EAEC O104:H4 strains in this outbreak and the strain of E. coli O104:H4 associated with a large outbreak of haemolytic ureamic syndrome in Germany in 2011. Further analysis of the EAEC plasmids, encoding the key enteroaggregative virulence genes, showed diversity with respect to FIB/FII type, gene content and genomic architecture. Known EAEC virulence genes, such as aggR, aat and aap, were present in all but one of the strains. A variety of fimbrial genes were observed, including genes encoding all five known fimbrial types, AAF/1 to AAF/V. The AAI operon was present in its entirety in 15 of the EAEC strains, absent in three and present, but incomplete, in two isolates. EAEC is known to be a diverse pathotype and this study demonstrates that a high level of diversity in strains recovered from cases associated with a single outbreak. Although the EAEC in this study did not carry the stx genes, this outbreak provides further evidence of the pathogenic potential of the EAEC O104:H4 serotype.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
We compared genomes from multiple isolations of Shiga toxin-producing
Escherichia coli
(STEC) O157:H7 from the same patient, in cases notified to Public Health England (PHE) between 2015 and 2019. ...There were 261 cases where multiple isolates were sequenced from the same patient comprising 589 isolates. Serial isolates from the same patient fell within five single nucleotide polymorphisms (SNPs) of each other for 260/261 (99.6%) of the cases, indicating that there was little evidence of within host variation. The investigation into the 13 SNP discrepancy between one isolate pair revealed the cause to be a recombination event within a
stx2a
-encoding prophage resulting in the insertion/deletion of a fragment of the genome. This 50 kbp prophage fragment was homologous to a prophage in the reference genome, and the short reads from the isolate that had the 50 kbp fragment, mapped unambiguously to this region. The discrepant variants in the isolate without the 50 kbp fragment were attributed to ambiguous mapping of the short reads from other prophage regions to the 50 kbp fragment in the reference genome. Identification of such recombination events in this dataset appeared to be rare, most likely because the majority of prophage regions in the Sakai reference genome are masked during the analysis. Identification of SNPs under neutral selection, and masking recombination events, is a requirement for phylogenetic analysis used for public health surveillance, and for the detection of point source outbreaks. However, assaying the accessory genome by combining the use of short and long read technologies for public health surveillance may provide insight into how recombination events impact on the evolutionary course of STEC O157:H7.
The use of whole genome sequencing (WGS) as a method for supporting outbreak investigations, studying
microbial populations and improving understanding of pathogenicity has been well-described (1-3). ...However, performing WGS on a discrete dataset does not pose the same challenges as implementing WGS as a routine, reference microbiology service for public health surveillance. Challenges include translating WGS data into a useable format for laboratory reporting, clinical case management,
surveillance, and outbreak investigation as well as meeting the requirement to communicate that information in an understandable and universal language for clinical and public health action. Public Health England have been routinely sequencing all referred presumptive
isolates since 2014 which has transformed our approach to reference microbiology and surveillance. Here we describe an overview of the integrated methods for cross-disciplinary working, describe the challenges and provide a perspective on how WGS has impacted the laboratory and surveillance processes in England and Wales.
Campylobacteriosis typically manifests as a short-lived, self-limiting gastrointestinal infection in humans, however prolonged infection can be seen in cases with underlying immunodeficiency. Public ...Health England received 25 isolates of Campylobacter jejuni from an individual with combined variable immunodeficiency over a period of 15 years. All isolates were typed and archived at the time of receipt. Whole genome sequencing (WGS) and antimicrobial susceptibility testing were performed to examine the relatedness of the isolates and to investigate the changes in the genome that had taken place over the course of the infection. Genomic typing methods were compared to conventional phenotypic methods, and revealed that the infection was caused by a single, persistent strain of C. jejuni belonging to clonal complex ST-45, with evidence of adaptation and selection in the genome over the course of the infection. Genomic analysis of sequence variants associated with antimicrobial resistance identified the genetic background behind rRNA gene mutations causing variable levels of resistance to erythromycin. This application of WGS to examine a persistent case of campylobacteriosis provides insight into the mutations and selective pressures occurring over the course of an infection, some of which have important clinical relevance.
•In August 2020, an outbreak of Shiga toxin-producing Escherichia coli O157 occurred in the United Kingdom.•Whole genome sequencing revealed that 36 cases formed a genetically distinct ...cluster.•Epidemiological evidence suggested a fast-food product was a likely cause of this outbreak.
In August 2020, an outbreak of Shiga toxin-producing Escherichia coli (STEC) O157:H7 occurred in the United Kingdom. Whole genome sequencing revealed that these cases formed a genetically distinct cluster.
Hypotheses generated from case interviews were tested in analytical studies, and results informed environmental sampling and food chain analysis. A case–case study used non-outbreak ‘comparison’ STEC cases; a case–control study used a market research panel to recruit controls.
A total of 36 cases were identified; all cases reported symptom onset between August 3 and August 16, 2020. The majority of cases (83%) resided in the Midlands region of England and in Wales. A high proportion of cases reported eating out, with one fast-food restaurant chain mentioned by 64% (n = 23) of cases. Both the case–case study (adjusted odds ratio (aOR) 31.8, 95% confidence interval (CI) 1.6–624.9) and the case–control study (aOR 9.19, 95% CI 1.0–82.8) revealed statistically significant results, showing that the consumption of a specific fast-food product was independently associated with infection.
Consumption of a specific fast-food product was a likely cause of this outbreak. The only ingredient specific to the product was cucumbers. The supply of cucumbers was immediately halted, and no further cases have been identified.
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