Mode and dynamics of <i>vanA</i>-type vancomycin-resistance dissemination in Dutch hospitals

Arredondo-Alonso, Sergio; Top, Janetta; Corander, Jukka; Willems, Rob J. L.; uumlrch, Anita C. Sch

doi:10.1101/2020.07.21.20158808

Cited by 3 publications

(3 citation statements)

References 63 publications

(94 reference statements)

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“…So far, genomic surveillance has focused on the signal provided by vertical evolution of pathogens to track spread of clones. Recent studies started using the high resolution offered by genomic surveillance to scrutinize the dynamics of dissemination of plasmids carrying resistance determinants within healthcare systems [64][65][66] . In this study, by combining epidemiological, functional genomics and evolutionary perspectives, we observed clonal and horizontal spread of a plasmid providing an innovative nutrient utilization trait, which could be adaptive under specific conditions.…”

Section: Enterococcimentioning

confidence: 99%

Genomic surveillance of vancomycin-resistantEnterococcus faeciumreveals spread of a linear plasmid conferring a nutrient utilization advantage

Boumasmoud

Haunreiter

Schweizer

et al. 2021

Preprint

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Healthcare-associated outbreaks of vancomycin-resistant Enterococcus faecium (VREfm) are a worldwide problem with increasing prevalence. The genomic plasticity of this hospital-adapted pathogen contributes to its efficient spread despite infection control measures. Here, we aimed to identify the genomic and phenotypic determinants of healthcare-associated transmission of VREfm. We assessed the VREfm transmission networks at the tertiary-care University Hospital of Zurich (USZ) between October 2014 and February 2018 and investigated microevolutionary dynamics of this pathogen. We performed whole-genome sequencing for the 69 VREfm isolates collected during this timeframe and assessed the population structure and variability of the vancomycin resistance transposon. Phylogenomic analysis allowed us to reconstruct transmission networks and to unveil external or indirect transmission networks, not detectable by traditional surveillance. Notably, it unveiled a persistent clone, sampled 31 times over a 29-month period. Exploring the evolutionary dynamics of this clone and characterizing the phenotypic consequences revealed the spread of a variant with decreased daptomycin susceptibility and the acquired ability to utilize N acetyl galactosamine (GalNAc), one of the primary constituents of the human gut mucins. This nutrient utilization advantage was conferred by a novel plasmid, termed pELF_USZ, which exhibited a linear topology. This plasmid, which was harbored by two distinct clones, was transferable by conjugation. Overall, this work provides an example of the potential of the integration of epidemiological, functional genomic and evolutionary perspectives to understand adaptation strategies contributing to the successful spread of VREfm.

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Section: Enterococcimentioning

confidence: 99%

Genomic surveillance of vancomycin-resistantEnterococcus faeciumreveals spread of a linear plasmid conferring a nutrient utilization advantage

Boumasmoud

Haunreiter

Schweizer

et al. 2021

Preprint

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“…The second class consists of tools that aim to recover distinct closed plasmid sequences. The output of these tools provides, in theory, a more comprehensive picture of the plasmid content of bacteria and allow to study the dissemination and epidemiology of specific plasmids [ 20 ].…”

Section: Introductionmentioning

confidence: 99%

Recovering Escherichia coli Plasmids in the Absence of Long-Read Sequencing Data

et al. 2021

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The incidence of infections caused by multidrug-resistant E. coli strains has risen in the past years. Antibiotic resistance in E. coli is often mediated by acquisition and maintenance of plasmids. The study of E. coli plasmid epidemiology and genomics often requires long-read sequencing information, but recently a number of tools that allow plasmid prediction from short-read data have been developed. Here, we reviewed 25 available plasmid prediction tools and categorized them into binary plasmid/chromosome classification tools and plasmid reconstruction tools. We benchmarked six tools (MOB-suite, plasmidSPAdes, gplas, FishingForPlasmids, HyAsP and SCAPP) that aim to reliably reconstruct distinct plasmids, with a special focus on plasmids carrying antibiotic resistance genes (ARGs) such as extended-spectrum beta-lactamase genes. We found that two thirds (n = 425, 66.3%) of all plasmids were correctly reconstructed by at least one of the six tools, with a range of 92 (14.58%) to 317 (50.23%) correctly predicted plasmids. However, the majority of plasmids that carried antibiotic resistance genes (n = 85, 57.8%) could not be completely recovered as distinct plasmids by any of the tools. MOB-suite was the only tool that was able to correctly reconstruct the majority of plasmids (n = 317, 50.23%), and performed best at reconstructing large plasmids (n = 166, 46.37%) and ARG-plasmids (n = 41, 27.9%), but predictions frequently contained chromosome contamination (40%). In contrast, plasmidSPAdes reconstructed the highest fraction of plasmids smaller than 18 kbp (n = 168, 61.54%). Large ARG-plasmids, however, were frequently merged with sequences derived from distinct replicons. Available bioinformatic tools can provide valuable insight into E. coli plasmids, but also have important limitations. This work will serve as a guideline for selecting the most appropriate plasmid reconstruction tool for studies focusing on E. coli plasmids in the absence of long-read sequencing data.

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“…The second class consists of tools that aim to recover distinct closed plasmid sequences. The output of these tools provide, in theory, a more comprehensive picture of the plasmid content of bacteria and allow to study the dissemination and epidemiology of specific plasmids [20].…”

Section: Introductionmentioning

confidence: 99%

Recovering Escherichia coli plasmids in the absence of long-read sequencing data

Paganini

Plantinga

Arredondo-Alonso

et al. 2021

Preprint

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The incidence of infections caused by multidrug-resistant Escherichia coli strains has risen in the past years. Antibiotic resistance in E. coli is often mediated by acquisition and maintenance of plasmids. The study of E. coli plasmid epidemiology and genomics often requires long-read sequencing information, but recently a number of tools that allow plasmid prediction from short-read data have been developed. Here, we reviewed 25 available plasmid prediction tools and categorized them into binary plasmid/chromosome classification tools and plasmid reconstruction tools. We benchmarked six tools that aim to reliably reconstruct distinct plasmids, with a special focus on plasmids carrying antibiotic resistance genes (ARGs) such as extended-spectrum beta-lactamase genes. They use either assembly graph information (plasmidSPAdes, gplas), reference databases (MOB-Suite, FishingForPlasmids) or both (HyAsP and SCAPP) to produce plasmid predictions. The benchmark data set consisted of 240 E. coli strains, harboring 631 plasmids, which were representative for the diversity of E. coli in public databases. Notably, these strains were not used for training any of the tools. We found that two thirds (n=425, 66.3.%) of all plasmids were correctly reconstructed by at least one of the six tools, with a range of 92 (14.58%) to 317 (50.23%) correctly predicted plasmids. However, the majority of plasmids that carried antibiotic resistance genes (n=85, 57.8%) could not be completely recovered as distinct plasmids by any of the tools. MOB-suite was the only tool that was able to correctly reconstruct the majority of plasmids (n=317, 50.23%), and performed best at reconstructing large plasmids (n=166, 46.37%) and ARG-plasmids (n=41, 27.9%), but predictions frequently contained chromosome contamination (40%). In contrast, plasmidSPAdes reconstructed the highest fraction of plasmids smaller than 18 kbp (n=168, 61.54%). Large ARG-plasmids, however, were recovered with small precision values (median=0.47, IQR=0.61), indicating that plasmidSPAdes frequently merged sequences derived from distinct replicons. Additionally, only 63% of all plasmid-borne ARGs were correctly predicted by plasmidSPAdes. The remaining four tools (FishingForPlasmids, HyAsP, SCAPP and gplas) were able to correctly reconstruct a combined total of 18 plasmids that were missed by MOB-suite and plasmidSPAdes. Available bioinformatic tools can provide valuable insight into E. coli plasmids, but also have important limitations. This work will serve as a guideline for selecting the most appropriate plasmid reconstruction tool for studies focusing on E. coli plasmids in the absence of long-read sequencing data.

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Mode and dynamics of vanA-type vancomycin-resistance dissemination in Dutch hospitals

Cited by 3 publications

References 63 publications

Genomic surveillance of vancomycin-resistantEnterococcus faeciumreveals spread of a linear plasmid conferring a nutrient utilization advantage

Genomic surveillance of vancomycin-resistantEnterococcus faeciumreveals spread of a linear plasmid conferring a nutrient utilization advantage

Recovering Escherichia coli Plasmids in the Absence of Long-Read Sequencing Data

Recovering Escherichia coli plasmids in the absence of long-read sequencing data

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