The identification of pathogens associated with respiratory symptoms other than the novel coronavirus disease 2019 (COVID-19) can be challenging. However, the diagnosis of pathogens is crucial for assessing the clinical outcome of patients. We comprehensively profiled pathogens causing non-COVID-19 respiratory symptoms during the 7th prevalent period in Gunma, Japan, using deep sequencing combined with a next-generation sequencer (NGS) and advanced bioinformatics technologies. The study included nasopharyngeal swabs from 40 patients who tested negative for severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) using immuno-chromatography and/or quantitative reverse transcription polymerase chain reaction (qRT-PCR) methods. Comprehensive pathogen sequencing was conducted through deep sequencing using NGS. Additionally, short reads obtained from NGS were analyzed for comprehensive pathogen estimation using MePIC (Metagenomic Pathogen Identification Pipeline for Clinical Specimens) and/or VirusTap. The results revealed the presence of various pathogens, including respiratory viruses and bacteria, in the present subjects. Notably, human adenovirus (HAdV) was the most frequently detected virus in 16 of the 40 cases (40.0%), followed by coryneforms, which were the most frequently detected bacteria in 21 of the 40 cases (52.5%). Seasonal human coronaviruses (NL63 type, 229E type, HKU1 type, and OC43 type), human bocaviruses, and human herpesviruses (human herpesvirus types 1-7) were not detected. Moreover, multiple pathogens were detected in 50% of the subjects. These results suggest that various respiratory pathogens may be associated with non-COVID-19 patients during the 7th prevalent period in Gunma Prefecture, Japan. Consequently, for an accurate diagnosis of pathogens causing respiratory infections, detailed pathogen analyses may be necessary. Furthermore, it is possible that various pathogens, excluding SARS-CoV-2, may be linked to fever and/or respiratory infections even during the COVID-19 pandemic.
Keywords: bioinformatics; next-generation sequencer; non-COVID-19 outpatients; pathogen profiles.