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Metatranscriptomic analysis of pediatric acute sinusitis: pathogen detection and host response profiling

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Date

2024-05-08

Authors

Abu Mazen, Nooran

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University of Waterloo

Abstract

Acute sinusitis (AS) is the fifth leading cause of antibiotic prescriptions in children. Distinguishing bacterial AS from common viral upper respiratory infections in children is crucial to prevent unnecessary antibiotic use but is challenging with current diagnostic methods. Despite its speed and cost, untargeted RNA sequencing (RNA-seq) of clinical samples from children with suspected AS has the potential to overcome several limitations of other methods. However, the utility of sequencing based approaches in analysis of AS has not been fully explored. Here, we performed RNA-seq of nasopharyngeal samples from 221 children with clinically diagnosed AS to characterize their pathogen and host-response profiles. Results from RNA-seq were compared with those obtained using culture for three common bacterial pathogens and qRT-PCR for 12 respiratory viruses. Metatranscriptomic pathogen detection showed high concordance with culture or qRT-PCR, showing 87%/81% sensitivity (sens) / specificity (spec) for detecting bacteria, and 86%/92% (sens/spec) for viruses, respectively. 22 additional pathogens not tested for in the clinical panel were detected, and plausible pathogens were identified in 11/19 (58%) of cases where no organism was detected by culture or qRT-PCR. 205 viruses were assembled across the samples including novel strains of coronaviruses, respiratory syncytial virus (RSV), and enterovirus D68. By analyzing host gene expression, host-response signatures were identified that distinguished bacterial and viral infections and correlated with pathogen abundance. Ultimately, this study demonstrates the potential of untargeted metatranscriptomics for in depth analysis of the etiology of AS, comprehensive host-response profiling, and using these together to work towards optimized patient care.

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Keywords

Bioinformatics, Metatranscriptomics, Sequencing, Acute sinusitis, Genomics, RNA, Host response, Pathogen detection

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