Analysis of Lung Microbiome in COVID-19 Patients during Time of Hospitalization

Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the pathogenic agent of the rapidly spreading pneumonia called coronavirus disease 2019 (COVID-19), primarily infects the respiratory and digestive tract. Several studies have indicated the alterations of the bacteria...

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Bibliographic Details
Main Authors: Linlin Xie, Liangjun Chen, Xinran Li, Junying Zhou, Hongpan Tian, Jin Zhao, Zhiqiang Li, Yirong Li
Format: Article
Language:English
Published: MDPI AG 2023-07-01
Series:Pathogens
Subjects:
Online Access:https://www.mdpi.com/2076-0817/12/7/944
Description
Summary:Background: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is the pathogenic agent of the rapidly spreading pneumonia called coronavirus disease 2019 (COVID-19), primarily infects the respiratory and digestive tract. Several studies have indicated the alterations of the bacterial microbiome in the lower respiratory tract during viral infection. However, both bacterial and fungal microbiota in the lung of COVID-19 patients remained to be explored. Methods: In this study, we conducted nanopore sequencing analyses of the lower respiratory tract samples from 38 COVID-19 patients and 26 non-COVID-19 pneumonia controls. Both bacterial and fungal microbiome diversities and microbiota abundances in the lung were compared. Results: Our results revealed significant differences in lung microbiome between COVID-19 patients and non-COVID-19 controls, which were strongly associated with SARS-CoV-2 infection and clinical status. COVID-19 patients exhibited a notably higher abundance of opportunistic pathogens, particularly <i>Acinetobacter baumannii</i> and <i>Candida</i> spp. Furthermore, the potential pathogens enriched in COVID-19 patients were positively correlated with inflammation indicators. Conclusions: Our study highlights the differences in lung microbiome diversity and composition between COVID-19 patients and non-COVID-19 patients. This may contribute to predicting co-pathogens and selecting optimal treatments for respiratory infections caused by SARS-CoV-2.
ISSN:2076-0817