Host lung gene expression patterns predict infectious etiology in a mouse model of pneumonia.

Respiratory Research
S E EvansBurton F Dickey

Abstract

Lower respiratory tract infections continue to exact unacceptable worldwide mortality, often because the infecting pathogen cannot be identified. The respiratory epithelia provide protection from pneumonias through organism-specific generation of antimicrobial products, offering potential insight into the identity of infecting pathogens. This study assesses the capacity of the host gene expression response to infection to predict the presence and identity of lower respiratory pathogens without reliance on culture data. Mice were inhalationally challenged with S. pneumoniae, P. aeruginosa, A. fumigatus or saline prior to whole genome gene expression microarray analysis of their pulmonary parenchyma. Characteristic gene expression patterns for each condition were identified, allowing the derivation of prediction rules for each pathogen. After confirming the predictive capacity of gene expression data in blinded challenges, a computerized algorithm was devised to predict the infectious conditions of subsequent subjects. We observed robust, pathogen-specific gene expression patterns as early as 2 h after infection. Use of an algorithmic decision tree revealed 94.4% diagnostic accuracy when discerning the presence of bacterial infec...Continue Reading

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Citations

Oct 30, 2013·American Journal of Respiratory Cell and Molecular Biology·Miriam H van LieshoutTom van der Poll
Feb 24, 2015·Frontiers in Microbiology·Yamilé López HernándezIsidre Gibert
Jun 1, 2017·Frontiers in Microbiology·Guillaume Desoubeaux, Carolyn Cray

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Datasets Mentioned

BETA
GSE15869

Methods Mentioned

BETA
lavage
scraping
ELISA
biopsy
bronchoalveolar lavage

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