Consulta: creatorFacets:"Munck, Nanna"
Registros recuperados: 2
Data/hora: 03/06/2024 07:22:49

Four European Salmonella Typhimurium datasets collected to develop WGS-based source attribution methods
Provedor de dados: 5
Autores: Munck, Nanna; Leekitcharoenphon, Pimlapas; Litrup, Eva; Kaas, Rolf; Meinen, Anika; Guillier, Laurent; Tang, Yue; Malorny, Burkhard; Palma, Federica; Borowiak, Maria; Gourmelon, Michele; Simon, Sandra; Banerji, Sangeeta; Petrovska, Liljana; Dallman, Timothy J.; Hald, Tine.
Zoonotic Salmonella causes millions of human salmonellosis infections worldwide each year. Information about the source of the bacteria guides risk managers on control and preventive strategies. Source attribution is the effort to quantify the number of sporadic human cases of a specific illness to specific sources and animal reservoirs. Source attribution methods for Salmonella have so far been based on traditional wet-lab typing methods. With the change to whole genome sequencing there is a need to develop new methods for source attribution based on sequencing data. Four European datasets collected in Denmark (DK), Germany (DE), the United Kingdom (UK) and France (FR) are presented in this descriptor. The datasets contain sequenced samples of Salmonella...
Tipo: Text
Ano: 2020
URL: https://archimer.ifremer.fr/doc/00612/72437/71383.pdf

AB_SA: Accessory genes-Based Source Attribution – tracing the source of Salmonella enterica Typhimurium environmental strains
Provedor de dados: 5
Autores: Guillier, Laurent; Gourmelon, Michele; Lozach, Solen; Cadel-six, Sabrina; Vignaud, Marie-léone; Munck, Nanna; Hald, Tine; Palma, Federica.
The partitioning of pathogenic strains isolated in environmental or human cases to their sources is challenging. The pathogens usually colonize multiple animal hosts, including livestock, which contaminate the food-production chain and the environment (e.g. soil and water), posing an additional public-health burden and major challenges in the identification of the source. Genomic data opens up new opportunities for the development of statistical models aiming to indicate the likely source of pathogen contamination. Here, we propose a computationally fast and efficient multinomial logistic regression source-attribution classifier to predict the animal source of bacterial isolates based on ‘source-enriched’ loci extracted from the accessory-genome profiles...
Tipo: Text
Palavras-chave: Environmental contamination; Multinomial logistic regression; Pangenome-wide enrichment analysis; Source attribution; Salmonella Typhimurium.
Ano: 2020
URL: https://archimer.ifremer.fr/doc/00624/73632/73072.pdf