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A Genome-Based Model to Predict the Virulence of Pseudomonas aeruginosa Isolates.

mBio - 25 Aug 2020

Pincus Nathan B, Ozer Egon A, Allen Jonathan P, Nguyen Marcus, Davis James J, Winter Deborah R, Chuang Chih-Hsien, Chiu Cheng-Hsun, Zamorano Laura, Oliver Antonio, Hauser Alan R

Abstract excerpt

Variation in the genome of Pseudomonas aeruginosa, an important pathogen, can have dramatic impacts on the bacterium's ability to cause disease. We therefore asked whether it was possible to predict the virulence of P. aeruginosa isolates based on their genomic content. We applied a machine learning approach to a genetically and phenotypically diverse collection of 115 clinical P. aeruginosa isolates using...

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Identifiers

PMID: 32843552
DOI: 10.1128/mBio.01527-20
PMCID: PMC7448275

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