High performance Legionella pneumophila source attribution using genomics-based machine learning classification.

ABSTRACT: Fundamental to effective Legionnaires' disease outbreak control is the ability to rapidly identify the environmental source(s) of the causative agent, Legionella pneumophila. Genomics has revolutionized pathogen surveillance, but L. pneumophila has a complex ecology and population structure that can limit source inference based on standard core genome phylogenetics. Here, we present a powerful machine learning approach that assigns the geographical source of Legionnaires' disease outbreaks more accurately than current core genome comparisons. Models were developed upon 534 L. pneumophila genome sequences, including 149 genomes linked to 20 previously reported Legionnaires' disease outbreaks through detailed case investigations. Our classification models were dev

SUBMITTER: Buultjens AH 

PROVIDER: S-EPMC10952463 | biostudies-literature | 2024 Mar

REPOSITORIES: biostudies-literature