Microbial Ecological Signatures Predict Pathogen Emergence and Multidrug Resistance in Cystic Fibrosis Airways up to a Year in Advance.

ABSTRACT: Chronic infections in cystic fibrosis (CF) emerge from gradual ecological transitions in the airway microbiome, yet early predictive markers remain poorly defined. We developed a new autoencoder-based framework that outperforms read-based or metagenome-assembled genome-based analyses at capturing the continuum from health-associated commensals to pathogen-dominated, antibiotic-tolerant communities. This improvement is achieved by integrating taxonomic and functional data from 127 sputum and bronchoalveolar lavage metagenomes from 64 people with CF into latent "Clusters of Phylogeny and Functions" (COPFs). Coupled with gradient-boosted random forests, COPFs predicted Pseudomonas aeruginosa colonisation, multidrug resistance, and impending infection up to a year before clinical detect

SUBMITTER: Goddard TR 

PROVIDER: S-EPMC12772665 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature