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VicPred: A Vibrio cholerae Genotype Prediction Tool.
Lee, Imchang; Ha, Sung-Min; Baek, Min-Gyung; Kim, Dong Wook; Yi, Hana; Chun, Jongsik.
Afiliação
  • Lee I; School of Biological Sciences, Seoul National University, Seoul, South Korea.
  • Ha SM; Institute for Biomaterials, Korea University, Seoul, South Korea.
  • Baek MG; School of Biological Sciences, Seoul National University, Seoul, South Korea.
  • Kim DW; Interdisciplinary Program in Precision Public Health, Korea University, Seoul, South Korea.
  • Yi H; Department of Public Health Sciences, Korea University, Seoul, South Korea.
  • Chun J; Department of Pharmacy, College of Pharmacy, Institute of Pharmacological Research, Hanyang University, Ansan, South Korea.
Front Microbiol ; 12: 691895, 2021.
Article em En | MEDLINE | ID: mdl-34566903
ABSTRACT
Genomic information can be used to predict major pathogenic traits of pathogens without the need for laboratory experimentation. However, no Vibrio cholerae genome-based trait identification tools currently exist. The aim of this study was to develop a web-based prediction tool to identify Vibrio pathogenic traits using publicly available 796 whole-genome sequences of V. cholerae. Using this application, 68 structural O-antigen gene clusters belonging to 49 serogroups of V. cholerae were classified, and the composition of the genes within the O-antigen cluster of each serogroup was identified. The arrangement and location of the CTX prophage and related elements of the seventh cholera pandemic strains were also revealed. With the versatile tool, named VicPred, we analyzed the assemblage of various SXTs (sulfamethoxazole/trimethoprim resistance element) and major genomic islands (GIs) of V. cholerae, and the increasing trend in drug-resistance revealing high resistance of the V. cholerae strains to certain antibiotics. The pathogenic traits of newly sequenced V. cholerae strains could be analyzed based on these characteristics. The accumulation of further genome data will expedite the establishment of a more precise genome-based pathogenic traits analysis tool.
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Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 3_ND Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Microbiol Ano de publicação: 2021 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Contexto em Saúde: 3_ND Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Revista: Front Microbiol Ano de publicação: 2021 Tipo de documento: Article