Comparison of the respiratory tract microbiome in hospitalized COVID-19 patients with different disease severity.

Abstract

Little is known about the characteristics of respiratory tract microbiome in Coronavirus disease 2019 (COVID-19) inpatients with different severity. We conducted a study that expected to clarify these characteristics as much as possible. A cross-sectional study was conducted to characterize respiratory tract microbial communities of 69 COVID-19 inpatients from 64 nasopharyngeal swabs and 5 sputum specimens using 16S ribosomal RNA gene V3-V4 region sequencing. The bacterial profiles were analyzed to find potential biomarkers by the two-step method, the combination of random forest model and the linear discriminant analysis effect size, and explore the connections with clinical characteristics by Spearman's rank test. Compared with mild COVID-19 patients, severe patients had significantly decreased bacterial diversity (p-values were less than 0.05 in the alpha and beta diversity) and relative lower abundance of opportunistic pathogens, including Actinomyces, Prevotella, Rothia, Streptococcus, Veillonella. Eight potential biomarkers including Treponema, Leptotrichia, Lachnoanaerobaculum, Parvimonas, Alloprevotella, Porphyromonas, Gemella, and Streptococcus were found to distinguish the mild COVID-19 patients from the severe COVID-19 patients. The genera of Actinomyces and Prevotella were negatively correlated with age in two groups. Intensive care unit admission, neutrophil count, and lymphocyte count were significantly correlated with different genera in the two groups. In addition, there was a positive correlation between Klebsiella and white blood cell count in two groups. The respiratory tract microbiome had significant differences in COVID-19 patients with different severity. The value of the respiratory tract microbiome as predictive biomarkers for COVID-19 severity deserves further exploration.

• Authors: Jiali Chen, Xiong Liu, Wei Liu, Chaojie Yang, Ruizhong Jia, Yuehua Ke, Jinpeng Guo, Leili Jia, Changjun Wang, Yong Chen
• Journal: Journal of medical virology (J Med Virol) Vol. 94 Issue 11 Pg. 5284-5293 (11 2022) ISSN: 1096-9071 [Electronic] United States
• PMID: 35838111 (Publication Type: Journal Article, Research Support, Non-U.S. Gov't)
• Copyright: © 2022 Wiley Periodicals LLC.

Topics

• Bacteria (genetics)
• COVID-19 (diagnosis)
• Cross-Sectional Studies
• Humans
• Microbiota (genetics)
• Respiratory System
• Severity of Illness Index