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Shiga-toxin-producing Escherichia coli (STEC) infection is an important global cause of foodborne disease. To date however, genomics-based studies of STEC have been predominately focused upon STEC collected in the Northern Hemisphere. Here, we demonstrate the population structure of 485 STEC isolates in Australia, and show that several clonal groups (CGs) common to Australia were infrequently detected in a representative selection of contemporary STEC genomes from around the globe. Further, phylogenetic analysis demonstrated that lineage II of the global O157:H7 STEC was most prevalent in Australia, and was characterized by a frameshift mutation in flgF, resulting in the H-non-motile phenotype. Strong concordance between in silico and phenotypic serotyping was observed, along with concordance between in silico and conventional detection of stx genes. These data represent the most comprehensive STEC analysis from the Southern Hemisphere, and provide a framework for future national genomics-based surveillance of STEC in Australia.

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We examined whether genomic surveillance of Escherichia coli in wastewater could capture the dominant E. coli lineages associated with bloodstream infection and livestock in the East of England, together with the antibiotic-resistance genes circulating in the wider E. coli population. Treated and untreated wastewater was taken from 20 municipal treatment plants in the East of England, half in direct receipt of acute hospital waste. All samples were culture positive for E. coli , and all but one were positive for extended-spectrum β-lactamase (ESBL)-producing E. coli . The most stringent wastewater treatment (tertiary including UV light) did not eradicate ESBL- E. coli in 2/3 cases. We sequenced 388 E. coli (192 ESBL, 196 non-ESBL). Multilocus sequence type (ST) diversity was similar between plants in direct receipt of hospital waste versus the remainder (93 vs 95 STs, respectively). We compared the genomes of wastewater E. coli with isolates from bloodstream infection (n=437), and livestock farms and retail meat (n=431) in the East of England. A total of 19/20 wastewater plants contained one or more of the three most common STs associated with bloodstream infection (ST131, ST73, ST95), and 14/20 contained the most common livestock ST (ST10). In an analysis of 1254 genomes (2 cryptic E. coli were excluded), wastewater isolates were distributed across the phylogeny and intermixed with isolates from humans and livestock. Ten bla CTX-M elements were identified in E. coli isolated from wastewater, together with a further 47 genes encoding resistance to the major antibiotic drug groups. Genes encoding resistance to colistin and the carbapenems were not detected. Genomic surveillance of E. coli in wastewater could be used to monitor new and circulating lineages and resistance determinants of public-health importance.

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Shigella species are a major cause of gastroenteritis worldwide, and Shigella sonnei is the most common species isolated within the United States. Previous surveillance work in Pennsylvania documented increased antimicrobial resistance (AMR) in S. sonnei associated with reported illnesses. The present study examined a subset of these isolates by whole genome sequencing (WGS) to determine the relationship between domestic and international isolates, to identify genes that may be useful for identifying specific Global Lineages of S. sonnei and to test the accuracy of WGS for predicting AMR phenotype. A collection of 22 antimicrobial-resistant isolates from patients infected within the United States or while travelling internationally between 2009 and 2014 was chosen for WGS. Phylogenetic analysis revealed both international and domestic isolates were one of two previously defined Global Lineages of S. sonnei , designated Lineage II and Lineage III. Twelve of 17 alleles tested distinguish these two lineages. Lastly, genome analysis was used to identify AMR determinants. Genotypic analysis was concordant with phenotypic resistance for six of eight antibiotic classes. For aminoglycosides and trimethoprim, resistance genes were identified in two and three phenotypically sensitive isolates, respectively. This article contains data hosted by Microreact.

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Bacteria are highly diverse, even within a species; thus, there have been many studies which classify a single species into multiple types and analyze the genetic differences between them. Recently, the use of whole-genome sequencing (WGS) has been popular for these analyses, and the identification of single-nucleotide polymorphisms (SNPs) between isolates is the most basic analysis performed following WGS. The performance of SNP-calling methods therefore has a significant effect on the accuracy of downstream analyses, such as phylogenetic tree inference. In particular, when closely related isolates are analyzed, e.g. in outbreak investigations, some SNP callers tend to detect a high number of false-positive SNPs compared with the limited number of true SNPs among isolates. However, the performances of various SNP callers in such a situation have not been validated sufficiently. Here, we show the results of realistic benchmarks of commonly used SNP callers, revealing that some of them exhibit markedly low accuracy when target isolates are closely related. As an alternative, we developed a novel pipeline BactSNP, which utilizes both assembly and mapping information and is capable of highly accurate and sensitive SNP calling in a single step. BactSNP is also able to call SNPs among isolates when the reference genome is a draft one or even when the user does not input the reference genome. BactSNP is available at https://github.com/IEkAdN/BactSNP.

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Antibiotic resistance reservoirs within food-producing animals are thought to be a risk to animal and human health. This study describes the minimum natural resistome of pig faeces as the bacteria are under no direct antibiotic selective pressure. The faecal resistome of 257 different genes comprised 56 core and 201 accessory resistance genes. The genes present at the highest relative abundances across all samples were tetW, tetQ, tet44, tet37, tet40, mefA, aadE, ant(9)−1, ermB and cfxA2. This study characterized the baseline resistome, the microbiome composition and the metabolic components described by the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways in healthy pig faeces, without antibiotic selective pressures. The microbiome hierarchical analysis resulted in a cluster tree with a highly similar pattern to that of the accessory resistome cluster tree. Functional capacity profiling identified genes associated with horizontal gene transfer. We identified a statistically significant positive correlation between the total antibiotic resistome and suggested indicator genes, which agree with using these genes as indicators of the total resistomes. The correlation between total resistome and total microbiome in this study was positive and statistically significant. Therefore, the microbiome composition influenced the resistome composition. This study identified a core and accessory resistome present in a cohort of healthy pigs, in the same conditions without antibiotics. It highlights the presence of antibiotic resistance in the absence of antibiotic selective pressure and the variability between animals even under the same housing, food and living conditions. Antibiotic resistance will remain in the healthy pig gut even when antibiotics are not used. Therefore, the risk of antibiotic resistance transfer from animal faeces to human pathogens or the environment will remain in the absence of antibiotics.

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The surveillance of antimicrobial-resistant isolates has proven to be one of the most valuable tools to understand the global rise of multidrug-resistant bacterial pathogens. We report the first insights into the current situation in the Caribbean, where a pilot project to monitor antimicrobial resistance (AMR) through phenotypic resistance measurements combined with whole-genome sequencing was set up in collaboration with the Caribbean Public Health Agency (CARPHA). Our first study focused on Klebsiella pneumoniae , a highly relevant organism amongst the Gram-negative opportunistic pathogens worldwide causing hospital- and community-acquired infections. Our results show that not only carbapenem resistance, but also hypervirulent strains, are circulating in patients in the Caribbean. Our current data does not allow us to infer their prevalence in the population. We argue for the urgent need to further support AMR surveillance and stewardship in this almost uncharted territory, which can make a significant impact on the reduction of antimicrobial usage. This article contains data hosted by Microreact (https://microreact.org).

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Carbapenem-resistant Klebsiella pneumoniae (CRKP) increasingly cause high-mortality outbreaks in hospital settings globally. Following a patient fatality at a hospital in Beijing due to a bla KPC-2-positive CRKP infection, close monitoring was put in place over the course of 14 months to characterize all bla KPC-2-positive CRKP in circulation in the hospital. Whole genome sequences were generated for 100 isolates from bla KPC-2-positive isolates from infected patients, carriers and the hospital environment. Phylogenetic analyses identified a closely related cluster of 82 sequence type 11 (ST11) isolates circulating in the hospital for at least a year prior to admission of the index patient. The majority of inferred transmissions for these isolates involved patients in intensive care units. Whilst the 82 ST11 isolates collected during the surveillance effort all had closely related chromosomes, we observed extensive diversity in their antimicrobial resistance (AMR) phenotypes. We were able to reconstruct the major genomic changes underpinning this variation in AMR profiles, including multiple gains and losses of entire plasmids and recombination events between plasmids, including transposition of bla KPC-2. We also identified specific cases where variation in plasmid copy number correlated with the level of phenotypic resistance to drugs, suggesting that the number of resistance elements carried by a strain may play a role in determining the level of AMR. Our findings highlight the epidemiological value of whole genome sequencing for investigating multi-drug-resistant hospital infections and illustrate that standard typing schemes cannot capture the extraordinarily fast genome evolution of CRKP isolates.

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Phenotypic change is a hallmark of bacterial adaptation during chronic infection. In the case of chronic Pseudomonas aeruginosa lung infection in patients with cystic fibrosis, well-characterized phenotypic variants include mucoid and small colony variants (SCVs). It has previously been shown that SCVs can be reproducibly isolated from the murine lung following the establishment of chronic infection with mucoid P. aeruginosa strain NH57388A. Using a combination of single-molecule real-time (PacBio) and Illumina sequencing we identify a large genomic inversion in the SCV through recombination between homologous regions of two rRNA operons and an associated truncation of one of the 16S rRNA genes and suggest this may be the genetic switch for conversion to the SCV phenotype. This phenotypic conversion is associated with large-scale transcriptional changes distributed throughout the genome. This global rewiring of the cellular transcriptomic output results in changes to normally differentially regulated genes that modulate resistance to oxidative stress, central metabolism and virulence. These changes are of clinical relevance because the appearance of SCVs during chronic infection is associated with declining lung function.

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The ability to distinguish different circulating pathogen clones from each other is a fundamental requirement to understand the epidemiology of infectious diseases. Phylogenetic analysis of genomic data can provide a powerful platform to identify lineages within bacterial populations, and thus inform outbreak investigation and transmission dynamics. However, resolving differences between pathogens associated with low-variant (LV) populations carrying low median pairwise single nucleotide variant (SNV) distances remains a major challenge. Here we present rPinecone, an R package designed to define sub-lineages within closely related LV populations. rPinecone uses a root-to-tip directional approach to define sub-lineages within a phylogenetic tree according to SNV distance from the ancestral node. The utility of this software was demonstrated using both simulated outbreaks and real genomic data of two LV populations: a hospital outbreak of methicillin-resistant Staphylococcus aureus and endemic Salmonella Typhi from rural Cambodia. rPinecone identified the transmission branches of the hospital outbreak and geographically confined lineages in Cambodia. Sub-lineages identified by rPinecone in both analyses were phylogenetically robust. It is anticipated that rPinecone can be used to discriminate between lineages of bacteria from LV populations where other methods fail, enabling a deeper understanding of infectious disease epidemiology for public health purposes.

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