Evaluation of unbiased RNAseq as a diagnostic method in influenza virus positive respiratory samples

Unbiased, non-targeted metagenomic RNA sequencing has the advantage to detect known as well as unknown sequences and thus can significantly improve the detection of viral, bacterial, parasitic and fungal sequences in public health settings. In particular, in only 30-40% of respiratory specimen from patients with acute respiratory illness conventional diagnostic methods successfully identify the putative pathogenic agent. We applied unbiased metagenomic RNA sequencing (UMERS) to 24 diagnostic respiratory specimens (BAL, sputum and swab) of patients with seasonal influenza infection and 5 BAL samples from patients with pneumonia tested negative for Influenza to validate RNA sequencing as an unbiased, additional diagnostic method. We evaluated i) sensitivity and specificity, ii) the potential to retrieve comprehensive influenza virus genomic information and, iii) capability to detect known superinfecting pathogens. When compared to quantitative RT-PCR for Influenza virus sequences, UMERS displayed sensitivity and specificity values for BAL samples of 71 – 83% and 100 % respectively. Complete influenza virus genomes could be assembled from 10 samples. Furthermore, in 3/24 samples additional viral pathogens could be detected and 2/24 samples showed significantly increased abundance of individual bacterial species known to cause superinfections during influenza virus infection. Thus, analysis of respiratory samples from known or suspected influenza patients by UMERS provides multiple parallel information of clinical relevance.