Sabiia Seb
PortuguêsEspañolEnglish
Embrapa
        Busca avançada

Botão Atualizar


Botão Atualizar

Registro completo
Provedor de dados:  ArchiMer
País:  France
Título:  AB_SA: Accessory genes-Based Source Attribution – tracing the source of Salmonella enterica Typhimurium environmental strains
Autores:  Guillier, Laurent
Gourmelon, Michele
Lozach, Solen
Cadel-six, Sabrina
Vignaud, Marie-léone
Munck, Nanna
Hald, Tine
Palma, Federica
Data:  2020
Ano:  2020
Palavras-chave:  Environmental contamination
Multinomial logistic regression
Pangenome-wide enrichment analysis
Source attribution
Salmonella Typhimurium.
Resumo:  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 of a pangenomic dataset. Depending on the accuracy of the model’s self-attribution step, the modeller selects the number of candidate accessory genes that best fit the model for calculating the likelihood of (source) category membership. The Accessory genes-Based Source Attribution (AB_SA) method was applied to a dataset of strains of Salmonella enterica Typhimurium and its monophasic variant ( S . enterica 1,4,[5],12:i:-). The model was trained on 69 strains with known animal-source categories (i.e. poultry, ruminant and pig). The AB_SA method helped to identify 8 genes as predictors among the 2802 accessory genes. The self-attribution accuracy was 80 %. The AB_SA model was then able to classify 25 of the 29 S . enterica Typhimurium and S . enterica 1,4,[5],12:i:- isolates collected from the environment (considered to be of unknown source) into a specific category (i.e. animal source), with more than 85 % of probability. The AB_SA method herein described provides a user-friendly and valuable tool for performing source-attribution studies in only a few steps. AB_SA is written in R and freely available at https://github.com/lguillier/AB_SA.
Tipo:  Text
Idioma:  Inglês
Identificador:  https://archimer.ifremer.fr/doc/00624/73632/73072.pdf

https://archimer.ifremer.fr/doc/00624/73632/73073.xlsx

DOI:10.1099/mgen.0.000366

https://archimer.ifremer.fr/doc/00624/73632/
Editor:  Microbiology Society
Relação:  info:eu-repo/grantAgreement/EC/FP7/643476/EU//COMPARE
Formato:  application/pdf
Fonte:  Microbial Genomics (2057-5858) (Microbiology Society) In Press
Direitos:  info:eu-repo/semantics/openAccess

restricted use
Fechar
 

Empresa Brasileira de Pesquisa Agropecuária - Embrapa
Todos os direitos reservados, conforme Lei n° 9.610
Política de Privacidade
Área restrita

Embrapa
Parque Estação Biológica - PqEB s/n°
Brasília, DF - Brasil - CEP 70770-901
Fone: (61) 3448-4433 - Fax: (61) 3448-4890 / 3448-4891 SAC: https://www.embrapa.br/fale-conosco

Valid HTML 4.01 Transitional