AUTHOR=Duan Zhimei , Gao Yanqiu , Liu Bin , Sun Baohua , Li Shuangfeng , Wang Chenlei , Liu Dongli , Wang Kaifei , Zhang Ye , Lou Zheng , Xie Lixin , Xie Fei TITLE=The Application Value of Metagenomic and Whole-Genome Capture Next-Generation Sequencing in the Diagnosis and Epidemiological Analysis of Psittacosis JOURNAL=Frontiers in Cellular and Infection Microbiology VOLUME=Volume 12 - 2022 YEAR=2022 URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2022.872899 DOI=10.3389/fcimb.2022.872899 ISSN=2235-2988 ABSTRACT=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 five out of ten 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 has tripled and the base number was 12 fold larger comparing to clinical mNGS with 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 was demonstrated in early diagnosing psittacosis. It is the first study to use whole genome capture to analyze C. psittaci epidemiological information.