Metagenomic next-generation sequencing (mNGS) is a valuable technique for identifying pathogens. However, conventional mNGS requires the separate processing of
DNA and
RNA genomes, which can be resource- and time-intensive. To mitigate these impediments, we propose a novel method called
DNA/
RNA cosequencing that aims to enhance the efficiency of pathogen detection.
DNA/
RNA cosequencing uses reverse transcription of total
nucleic acids extracted from samples by using random primers, without removing
DNA, and then employs mNGS. We applied this method to 85 cases of severe acute
respiratory infections (SARI). Influenza virus was identified in 13 cases (H1N1: seven cases, H3N2: three cases, unclassified
influenza type: three cases) and was not detected in the remaining 72 samples. Bacteria were present in all samples. Pseudomonas aeruginosa, Klebsiella pneumoniae, and Acinetobacter baumannii were detected in four
influenza-positive samples, suggesting
coinfections. The sensitivity and specificity for detecting influenza A virus were 73.33% and 95.92%, respectively. A κ value of 0.726 indicated a high level of concordance between the results of
DNA/
RNA cosequencing and SARI influenza virus monitoring.
DNA/
RNA cosequencing enhanced the efficiency of pathogen detection, providing a novel capability to strengthen surveillance and thereby prevent and control infectious disease outbreaks.