Predictive signature of murine and human host response to typical and atypical pneumonia

Using gene expression data we developed a predictive signture to discriminate between typical bacterial, atyipcal bacterial, and viral pnuemonia in murine samples and validated it against open source human datasets. Male and Female C57BL/6j mice were exposed to streptococcs pneumoniae, mycoplasma pnuemoniae, and a murine strain of H1N1. Blood was collected for RNA expression analysis at predetermined time point. Amplified RNA was assyed using Affymetrix murine 430A2.0 microarrays containing 22,690 probes. Probe intensities were detected using Axon GenePix 4000B Scanner. These intensities were converted to an eset in the statitical program R. Differential gene expression was determined using the limma and empirical Bayes tool sets. Pathway analyis was performed using ReactomePA. We use LASSO to develope a predictive sigature to discriminate between these pneumonia types. This signature was validated on open source human datasets.