Integrated population clustering and genomic epidemiology with PopPIPE DOI Creative Commons
M. McHugh, Samuel Horsfield, Johanna von Wachsmann

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Дек. 9, 2024

Abstract Genetic distances between bacterial DNA sequences can be used to cluster populations into closely related subpopulations, and as an additional source of information when detecting possible transmission events. Due their variable gene content order, reference-free methods offer more sensitive detection genetic differences, especially among samples found in outbreaks. However, across longer distances, frequent recombination make calculation interpretation these differences challenging, requiring significant bioinformatic expertise manual intervention during the analysis process. Here we present a Pop ulation PIPE line (PopPIPE) which combines rapid genome analyse genomes two scales, splitting whole subclusters plausible events within clusters. We use k-mer sketching split strains, followed by removal create alignments strains. first show that this approach creates high quality on population-wide dataset Streptococcus pneumoniae . When applied nosocomial vancomycin resistant Enterococcus faecium samples, PopPIPE finds clusters are epidemiologically than core or MLST-based approaches. Our pipeline is reproducible, interactive visualisations, easily reconfigured re-run new datasets. Therefore provides user-friendly for analyses spanning species-wide clustering outbreak investigations. Impact statement As time passes, accumulate small changes sequence due mutations, larger horizontal transfer. Using sequences, it phylogenetics work out most likely order happened, how long they took happen. Then, one estimate separates any – if short then may have been directly transmitted acquired from same source; but must separately. This determine chains, conjunction with dates locations infections. Understanding chains enables targeted infection control measures. correctly calculating evidence made difficult distinguishing different types changes, dealing large amounts data, need multiple complex tools. addressed gap creating computational workflow, PopPIPE, automates process transmissions using sequences. applies state-of-the-art tools fast easy run making technology will available wider audience researchers. Data summary The code at https://github.com/bacpop/PopPIPE docker image https://hub.docker.com/r/poppunk/poppipe Raw sequencing reads isolates deposited NCBI under BioProject accession number PRJNA997588.

Язык: Английский

Integrated population clustering and genomic epidemiology with PopPIPE DOI Creative Commons
M. McHugh, Samuel Horsfield, Johanna von Wachsmann

и другие.

Microbial Genomics, Год журнала: 2025, Номер 11(4)

Опубликована: Апрель 28, 2025

Genetic distances between bacterial DNA sequences can be used to cluster populations into closely related subpopulations and as an additional source of information when detecting possible transmission events. Due their variable gene content order, reference-free methods offer more sensitive detection genetic differences, especially among samples found in outbreaks. However, across longer distances, frequent recombination make calculation interpretation these differences challenging, requiring significant bioinformatic expertise manual intervention during the analysis process. Here, we present a Pop ulation PIPE line (PopPIPE) which combines rapid genome analyse genomes two scales, splitting whole subclusters plausible events within clusters. We use k-mer sketching split strains, followed by removal create alignments strains. first show that this approach creates high-quality on population-wide dataset Streptococcus pneumoniae . When applied nosocomial vancomycin-resistant Enterococcus faecium samples, PopPIPE finds clusters are epidemiologically than core or multilocus sequence typing (MLST) approaches. Our pipeline is reproducible, interactive visualizations easily reconfigured re-run new datasets. Therefore, provides user-friendly for analyses spanning species-wide clustering outbreak investigations.

Язык: Английский

Процитировано

0
Spread of the novel vancomycin-resistant Enterococcus faecium strain ST1299/vanA from local level in Germany to cross-border level in Austria, 2018 to 2022 DOI Creative Commons
Anca Rath, Bärbel Kieninger,

Nilufarbayim Mirzaliyeva

и другие.

Eurosurveillance, Год журнала: 2025, Номер 30(20)

Опубликована: Май 22, 2025

Introduction Vancomycin-resistant Enterococcus faecium (VREfm) isolates of sequence type (ST)1299 were described recently in south-eastern German hospitals and rapidly expanded from local to cross-border level. Aim We describe the spread novel VREfm strain ST1299/vanA on a genetic, geographical temporal level during first 5 years after its detection. Methods At University Hospital Regensburg (UHoR), routine surveillance is whole genome sequencing-based (≥ 1 per van -genotype, patient year). In this observational cohort study, we analysed one ST1299 isolate our database (2016–2022) year. Isolates added Merciful Brothers (MBR), National Reference Centre for Staphylococci Enterococci (NRC), clinical Austria. Results identified 635 (100% vanA ), including 504 Regensburg, 113 blood cultures. detected 2018 simultaneously (n = 2) southern Bavaria 2), with (UHoR) regional numbers increasing 2020, shifting national scale same Genome data, by cgMLST, showed predominance ST1299/CT1903 (315/504 isolates, 62.5%) ST1299/CT3109 (127/504 25.2%) Regensburg. By 2021, reached Upper Austria causing hospital outbreaks 5). Phylogeny analysis suggests common ancestors ST80, ST18 ST17. Conclusion Since their emergence 2018, two highly transmissible subtypes ST1299/ national, then scale. The observed outbreak tendency may explain rapid successful high clonality collection.

Язык: Английский

Процитировано

0
Characterization of vanA-harboring plasmids supports differentiation of outbreak-related and sporadic vancomycin-resistant Enterococcus faecium isolates in a tertiary care hospital DOI Creative Commons

Adam Sobkowiak,

Natalie Effelsberg, Vincent van Almsick

и другие.

BMC Microbiology, Год журнала: 2025, Номер 25(1)

Опубликована: Май 28, 2025

Abstract Background The prevention of vancomycin-resistant Enterococcus faecium (VREfm) infections and transmissions poses a major challenge to hospitals. Vancomycin resistance can be plasmid encoded; however, as the analysis plasmids is challenging, so far only few reports have provided detailed characterization in nosocomial VREfm transmission. Here we describe outbreak caused by vanA positive ST80 isolate. sequence data was used distinguish outbreak-associated isolates from sporadic cases investigate spread this within local population. Methods 446 were collected routine surveillance between 01/2022 02/2024 analyzed using long-read whole genome sequencing (lrWGS). Genetic relatedness evaluated based on core multilocus typing (cgMLST). Genetically similar identified Mash approach. Results 30 genetically patients’ screening environmental samples. Infection control evaluation confirmed transmission through shared hospital rooms. All outbreak-related isolates, including samples, carried highly (Mash distance < 0.001) with an identical replicon type. After enhanced infection measures established, no new detected. Comparison additional respective department showed evidence for further Conclusions Our study illustrates how support similar, but could clearly distinguished other Taken together, hospital-associated improve our understanding epidemiology.

Язык: Английский

Процитировано

0
Integrated population clustering and genomic epidemiology with PopPIPE DOI Creative Commons
M. McHugh, Samuel Horsfield, Johanna von Wachsmann

и другие.

bioRxiv (Cold Spring Harbor Laboratory), Год журнала: 2024, Номер unknown

Опубликована: Дек. 9, 2024

Abstract Genetic distances between bacterial DNA sequences can be used to cluster populations into closely related subpopulations, and as an additional source of information when detecting possible transmission events. Due their variable gene content order, reference-free methods offer more sensitive detection genetic differences, especially among samples found in outbreaks. However, across longer distances, frequent recombination make calculation interpretation these differences challenging, requiring significant bioinformatic expertise manual intervention during the analysis process. Here we present a Pop ulation PIPE line (PopPIPE) which combines rapid genome analyse genomes two scales, splitting whole subclusters plausible events within clusters. We use k-mer sketching split strains, followed by removal create alignments strains. first show that this approach creates high quality on population-wide dataset Streptococcus pneumoniae . When applied nosocomial vancomycin resistant Enterococcus faecium samples, PopPIPE finds clusters are epidemiologically than core or MLST-based approaches. Our pipeline is reproducible, interactive visualisations, easily reconfigured re-run new datasets. Therefore provides user-friendly for analyses spanning species-wide clustering outbreak investigations. Impact statement As time passes, accumulate small changes sequence due mutations, larger horizontal transfer. Using sequences, it phylogenetics work out most likely order happened, how long they took happen. Then, one estimate separates any – if short then may have been directly transmitted acquired from same source; but must separately. This determine chains, conjunction with dates locations infections. Understanding chains enables targeted infection control measures. correctly calculating evidence made difficult distinguishing different types changes, dealing large amounts data, need multiple complex tools. addressed gap creating computational workflow, PopPIPE, automates process transmissions using sequences. applies state-of-the-art tools fast easy run making technology will available wider audience researchers. Data summary The code at https://github.com/bacpop/PopPIPE docker image https://hub.docker.com/r/poppunk/poppipe Raw sequencing reads isolates deposited NCBI under BioProject accession number PRJNA997588.

Язык: Английский

Процитировано

0