Metatranscriptomic profiling reveals pathogen and host response signatures of pediatric acute sinusitis and upper...

Acute sinusitis (AS) is a frequent cause of antibiotic prescriptions in children. Distinguishing bacterial AS from common viral upper respiratory infections (URIs) is crucial to prevent unnecessary antibiotic use but is challenging with current diagnostic methods. Despite its speed and cost, untargeted RNA sequencing of clinical samples from children with suspected AS has the potential to overcome several limitations of other methods. In addition, RNA-seq may reveal novel host-response biomarkers for development of future diagnostic assays that distinguish bacterial from viral infections. There are however no available RNA-seq datasets of pediatric AS that provide a comprehensive view of both pathogen etiology and host immune response.

Here, we performed untargeted RNA-seq (metatranscriptomics) of nasopharyngeal samples from 221 children with AS and performed a comprehensive analysis of pathogen etiology and the impact of bacterial and viral infections on host immune responses. Accuracy of RNA-seq-based pathogen detection was evaluated by comparison with culture tests for three common bacterial pathogens and qRT-PCR tests for 12 respiratory viruses. Host gene expression patterns were explored to identify potential host responses that distinguish bacterial from viral infections.

RNA-seq-based pathogen detection showed high concordance with culture or qRT-PCR, showing 87%/81% sensitivity (sens) / specificity (spec) for detecting three AS-associated bacterial pathogens, and 86%/92% (sens/spec) for detecting 12 URI-associated viruses, respectively. RNA-seq also detected an additional 22 pathogens not tested for clinically and identified plausible pathogens in 11/19 (58%) of cases where no organism was detected by culture or qRT-PCR. We reconstructed genomes of 196 viruses across the samples including novel strains of coronaviruses, respiratory syncytial virus, and enterovirus D68, which provide useful genomic data for ongoing pathogen surveillance programs. By analyzing host gene expression, we identified host-response signatures that differentiate bacterial and viral infections, revealing hundreds of candidate gene biomarkers for future diagnostic assays.

Our study provides a one-of-kind dataset that profiles the interplay between pathogen infection and host responses in pediatric AS and URI. It reveals bacterial and viral-specific host responses that could enable new diagnostic approaches and demonstrates the potential of untargeted RNA-seq in diagnostic analysis of AS and URI.