Background: To evaluate the value of metagenomic next-generation sequencing (mNGS) for the early diagnosis of psittacosis, and to investigate its epidemiology by whole-genome capture.
Methods: Twenty-one bronchoalveolar lavage fluid (BALF) and blood samples of 16 psittacosis patients from multiple centers during August 2019 to September 2021 were analyzed retrospectively. mNGS with normal datasets (10 M 75-bp single-end reads after sequencing) and larger datasets (30 M 150-bp paired-end reads after sequencing) as well as quantitative real-time polymerase chain reaction (qPCR) were used to detect the pathogen. Also, whole-genome capture of Chlamydophila psittaci was applied to draw the phylogenetic tree.
Results: mNGS successfully detected the pathogen in all 16 cases (100%), while qPCR was positive only in 5 out of 10 cases (50%), indicating a significantly higher sensitivity of mNGS than qPCR (p < 0.01). BALF-mNGS performed better than blood-mNGS (16/16 versus 3/5, p < 0.05). In addition, larger datasets (the read counts have tripled, and the base number was 12-fold larger compared to clinical mNGS with a normal dataset) of mNGS showed significantly increased contents of human DNA (p < 0.05) and decreased reads per million of the pathogen, suggesting no improvement. Whole-genome capture results of five samples (>60% coverage and >1 depth) were used to construct the phylogenetic tree.
Conclusion: Significant advantages of mNGS with normal datasets were demonstrated in early diagnosing psittacosis. It is the first study to use whole-genome capture to analyze C. psittaci epidemiological information.
Keywords: Chlamydophila psittaci; Psittacosis; capture; diagnosis; epidemiology; metagenomic next-generation sequencing.
Copyright © 2022 Duan, Gao, Liu, Sun, Li, Wang, Liu, Wang, Zhang, Lou, Xie and Xie.