Comparison of Shiga toxin-encoding bacteriophages in highly pathogenic strains of Shiga toxin-producing Escherichia coli O157:H7 in the UK

Over the last 35 years in the UK, the burden of Shiga toxin-producing Escherichia coli (STEC) O157:H7 infection has, during different periods of time, been associated with five different sub-lineages (1983-1995, Ia, I/IIa and I/IIb; 1996-2014, Ic; and 2015-2018, IIb). The acquisition of a stx2a-encoding bacteriophage by these five sub-lineages appears to have coincided with their respective emergences. The Oxford Nanopore Technologies (ONT) system was used to sequence, characterize and compare the stx-encoding prophages harboured by each sub-lineage to investigate the integration of this key virulence factor. The stx2a-encoding prophages from each of the lineages causing clinical disease in the UK were all different, including the two UK sub-lineages (Ia and I/IIa) circulating concurrently and causing severe disease in the early 1980s. Comparisons between the stx2a-encoding prophage in sub-lineages I/IIb and IIb revealed similarity to the prophage commonly found to encode stx2c, and the same site of bacteriophage integration (sbcB) as stx2c-encoding prophage. These data suggest independent acquisition of previously unobserved stx2a-encoding phage is more likely to have contributed to the emergence of STEC O157:H7 sub-lineages in the UK than intra-UK lineage to lineage phage transmission. In contrast, the stx2c-encoding prophage showed a high level of similarity across lineages and time, consistent with the model of stx2c being present in the common ancestor to extant STEC O157:H7 and maintained by vertical inheritance in the majority of the population. Studying the nature of the stx-encoding bacteriophage contributes to our understanding of the emergence of highly pathogenic strains of STEC O157:H7

Re-analysis of an outbreak of Shiga toxin-producing Escherichia coli O157:H7 associated with raw drinking milk using Nanopore sequencing

The aim of this study was to compare Illumina and Oxford Nanopore Technology (ONT) sequencing data to quantify genetic variation to assess within-outbreak strain relatedness and characterise microevolutionary events in the accessory genomes of a cluster of 23 genetically and epidemiologically linked isolates related to an outbreak of Shiga toxin-producing Escherichia coli O157:H7 caused by the consumption of raw drinking milk. There were seven discrepant variants called between the two technologies, five were false-negative or false-positive variants in the Illumina data and two were false-negative calls in ONT data. After masking horizontally acquired sequences such as prophages, analysis of both short and long-read sequences revealed the 20 isolates linked to the outbreak in 2017 had a maximum SNP distance of one SNP between each other, and a maximum of five SNPs when including three additional strains identified in 2019. Analysis of the ONT data revealed a 47 kbp deletion event in a terminal compound prophage within one sample relative to the remaining samples, and a 0.65 Mbp large chromosomal rearrangement (inversion), within one sample relative to the remaining samples. Furthermore, we detected two bacteriophages encoding the highly pathogenic Shiga toxin (Stx) subtype, Stx2a. One was typical of Stx2a-phage in this sub-lineage (Ic), the other was atypical and inserted into a site usually occupied by Stx2c-encoding phage. Finally, we observed an increase in the size of the pO157 IncFIB plasmid (1.6 kbp) in isolates from 2019 compared to those from 2017, due to the duplication of insertion elements within the plasmids from the more recently isolated strains. The ability to characterize the accessory genome in this way is the first step to understanding the significance of these microevolutionary events and their impact on the genome plasticity and virulence between strains of this zoonotic, foodborne pathogen.</p

New methods for unmixing sediment grain size data

Grain size distribution (GSD) data are widely used in Earth sciences and although large data sets are regularly generated, detailed numerical analyses are not routine. Unmixing GSDs into components can help understand sediment provenance and depositional regimes/processes. End-member analysis (EMA), which fits one set of end-members to a given data set, is a powerful way to unmix GSDs into geologically meaningful parts. EMA estimates end-members based on covariability within a data set and can be considered as a nonparametric approach. Available EMA algorithms, however, either produce suboptimal solutions or are time consuming. We introduce unmixing algorithms inspired by hyperspectral image analysis that can be applied to GSD data and which provide an improvement over current techniques. Nonparametric EMA is often unable to identify unimodal grain size subpopulations that correspond to single sediment sources. An alternative approach is single-specimen unmixing (SSU), which unmixes individual GSDs into unimodal parametric distributions (e.g., lognormal). We demonstrate that the inherent nonuniqueness of SSU solutions renders this approach unviable for estimating underlying mixing processes. To overcome this, we develop a new algorithm to perform parametric EMA, whereby an entire data set can be unmixed into unimodal parametric end-members (e.g., Weibull distributions). This makes it easier to identify individual grain size subpopulations in highly mixed data sets. To aid investigators in applying these methods, all of the new algorithms are available in AnalySize, which is GUI software for processing and unmixing grain size data

Use of Nanopore Sequencing to Characterise the Genomic Architecture of Mobile Genetic Elements Encoding bla CTX-M-15 in Escherichia coli Causing Travellers' Diarrhoea

Increasing levels of antimicrobial resistance (AMR) have been documented in Escherichia coli causing travellers’ diarrhoea, particularly to the third-generation cephalosporins. Diarrhoeagenic E. coli (DEC) can act as a reservoir for the exchange of AMR genes between bacteria residing in the human gut, enabling them to survive and flourish through the selective pressures of antibiotic treatments. Using Oxford Nanopore Technology (ONT), we sequenced eight isolates of DEC from four patients’ specimens who had all recently returned to the United Kingdome from Pakistan. Sequencing yielded two DEC harbouring bla(CTX-M-15) per patient, all with different sequence types (ST) and belonging to five different pathotypes. The study aimed to determine whether bla(CTX-M-15) was located on the chromosome or plasmid and to characterise the drug-resistant regions to better understand the mechanisms of onward transmission of AMR determinants. Patients A and C both had one isolate where bla(CTX-M-15) was located on the plasmid (899037 & 623213, respectively) and one chromosomally encoded (899091 & 623214, respectively). In patient B, bla(CTX-M-15) was plasmid-encoded in both DEC isolates (786605 & 7883090), whereas in patient D, bla(CTX-M-15) was located on the chromosome in both DEC isolates (542093 & 542099). The two bla(CTX-M-15)-encoding plasmids associated with patient B were different although the bla(CTX-M-15)-encoding plasmid isolated from 788309 (IncFIB) exhibited high nucleotide similarity to the bla(CTX-M-15)-encoding plasmid isolated from 899037 (patient A). In the four isolates where bla(CTX-M-15) was chromosomally encoded, two isolates (899091 & 542099) shared the same insertion site. The bla(CTX-M-15) insertion site in isolate 623214 was described previously, whereas that of isolate 542093 was unique to this study. Analysis of Nanopore sequencing data enables us to characterise the genomic architecture of mobile genetic elements encoding AMR determinants. These data may contribute to a better understanding of persistence and onward transmission of AMR determinants in multidrug-resistant (MDR) E. coli causing gastrointestinal and extra-intestinal infections

Analysis of a small outbreak of Shiga toxin-producing Escherichia coli O157:H7 using long-read sequencing

Compared to short-read sequencing data, long-read sequencing facilitates single contiguous de novo assemblies and characterization of the prophage region of the genome. Here, we describe our methodological approach to using Oxford Nanopore Technology (ONT) sequencing data to quantify genetic relatedness and to look for microevolutionary events in the core and accessory genomes to assess the within-outbreak variation of four genetically and epidemiologically linked isolates. Analysis of both Illumina and ONT sequencing data detected one SNP between the four sequences of the outbreak isolates. The variant calling procedure highlighted the importance of masking homologous sequences in the reference genome regardless of the sequencing technology used. Variant calling also highlighted the systemic errors in ONT base-calling and ambiguous mapping of Illumina reads that results in variations in the genetic distance when comparing one technology to the other. The prophage component of the outbreak strain was analysed, and nine of the 16 prophages showed some similarity to the prophage in the Sakai reference genome, including the stx2a-encoding phage. Prophage comparison between the outbreak isolates identified minor genome rearrangements in one of the isolates, including an inversion and a deletion event. The ability to characterize the accessory genome in this way is the first step to understanding the significance of these microevolutionary events and their impact on the evolutionary history, virulence and potentially the likely source and transmission of this zoonotic, foodborne pathogen

Clinical and public health implications of increasing notifications of LEE-negative Shiga toxin-producing Escherichia coli in England, 2014–2022

Introduction. Shiga toxin-producing Escherichia coli (STEC) belong to a diverse group of gastrointestinal pathogens. The pathogenic potential of STEC is enhanced by the presence of the pathogenicity island called the Locus of Enterocyte Effacement (LEE), including the intimin encoding gene eae. Gap statement. STEC serotypes O128:H2 (Clonal Complex [CC]25), O91:H14 (CC33), and O146:H21 (CC442) are consistently in the top five STEC serotypes isolated from patients reporting gastrointestinal symptoms in England. However, they are eae/LEE-negative and perceived to be a low risk to public health, and we know little about their microbiology and epidemiology. Aim. We analysed clinical outcomes and genome sequencing data linked to patients infected with LEE-negative STEC belonging to CC25 (O128:H2, O21:H2), CC33 (O91:H14) and, and CC442 (O146:H21, O174:H21) in England to assess the risk to public health. Results. There was an almost ten-fold increase between 2014 and 2022 in the detection of all STEC belonging to CC25, CC33 and CC442 (2014 n=38, 2022 n=336), and a total of 1417 cases. There was a higher proportion of female cases (55–70 %) and more adults than children, with patients aged between 20–40 and >70 most at risk across the different serotypes. Symptoms were consistent across the three dominant serotypes O91:H14 (CC33), O146:H21 (CC442) and O128:H2 (CC25) (diarrhoea >75 %; bloody diarrhoea 25–32 %; abdominal pain 64–72 %; nausea 37–45 %; vomiting 10–24 %; and fever 27–30 %). Phylogenetic analyses revealed multiple events of acquisition and loss of different stx-encoding prophage. Additional putative virulence genes were identified including iha, agn43 and subA. Conclusions. Continued monitoring and surveillance of LEE-negative STEC infections is essential due to the increasing burden of infectious intestinal disease, and the risk that highly pathogenic strains may emerge following acquisition of the Shiga toxin subtypes associated with the most severe clinical outcomes