AUTHOR=Meng Huan , Wang Shuang , Tang Xiaomeng , Guo Jingjing , Xu Xinming , Wang Dagang , Jin Fangfang , Zheng Mei , Yin Shangqi , He Chaonan , Han Ying , Chen Jin , Han Jinyu , Ren Chaobo , Gao Yantao , Liu Huifang , Wang Yajie , Jin Ronghua 

TITLE=Respiratory immune status and microbiome in recovered COVID-19 patients revealed by metatranscriptomic analyses

JOURNAL=Frontiers in Cellular and Infection Microbiology

VOLUME=12

YEAR=2022

URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2022.1011672

DOI=10.3389/fcimb.2022.1011672

ISSN=2235-2988

ABSTRACT=<p>Coronavirus disease 2019 (COVID-19) is currently a severe threat to global public health, and the immune response to COVID-19 infection has been widely investigated. However, the immune status and microecological changes in the respiratory systems of patients with COVID-19 after recovery have rarely been considered. We selected 72 patients with severe COVID-19 infection, 57 recovered from COVID-19 infection, and 65 with non-COVID-19 pneumonia, for metatranscriptomic sequencing and bioinformatics analysis. Accordingly, the differentially expressed genes between the infected and other groups were enriched in the chemokine signaling pathway, NOD-like receptor signaling pathway, phagosome, TNF signaling pathway, NF-kappa B signaling pathway, Toll-like receptor signaling pathway, and C-type lectin receptor signaling pathway. We speculate that <italic>IL17RD</italic>, CD74, and TNFSF15 may serve as disease biomarkers in COVID-19. Additionally, principal coordinate analysis revealed significant differences between groups. In particular, frequent co-infections with the genera <italic>Streptococcus</italic>, <italic>Veillonella</italic>, <italic>Gemella</italic>, and <italic>Neisseria</italic>, among others, were found in COVID-19 patients. Moreover, the random forest prediction model with differential genes showed a mean area under the curve (AUC) of 0.77, and <italic>KCNK12</italic>, <italic>IL17RD</italic>, <italic>LOC100507412</italic>, <italic>PTPRT</italic>, <italic>MYO15A</italic>, <italic>MPDZ</italic>, <italic>FLRT2</italic>, <italic>SPEG</italic>, <italic>SERPINB3</italic>, and <italic>KNDC1</italic> were identified as the most important genes distinguishing the infected group from the recovered group. <italic>Agrobacterium tumefaciens, Klebsiella michiganensis, Acinetobacter pittii, Bacillus</italic> sp. FJAT.14266, <italic>Brevundimonas naejangsanensis, Pseudopropionibacterium propionicum, Priestia megaterium, Dialister pneumosintes, Veillonella rodentium</italic>, and <italic>Pseudomonas protegens</italic> were selected as candidate microbial markers for monitoring the recovery of COVID patients. These results will facilitate the diagnosis, treatment, and prognosis of COVID patients recovering from severe illness.</p>