AUTHOR=Zhan Danting , Li Dan , Yuan Ke , Sun Yihua , He Lijuan , Zhong Jiacheng , Wang Lingwei 

TITLE=Characteristics of the pulmonary microbiota in patients with mild and severe pulmonary infection

JOURNAL=Frontiers in Cellular and Infection Microbiology

VOLUME=Volume 13 - 2023

YEAR=2023

URL=https://www.frontiersin.org/journals/cellular-and-infection-microbiology/articles/10.3389/fcimb.2023.1227581

DOI=10.3389/fcimb.2023.1227581

ISSN=2235-2988

ABSTRACT=Background: Lung infection is a global health problem associated with high morbidity, mortality, and increasing rates of hospitalization. The correlation between pulmonary microecology and infection severity remains unclear. Therefore, the purpose of this study was to investigate the differences in lung microecology and potential biomarkers in patients with mild and severe pulmonary infection.
Method: Patients with pulmonary infection or suspected infection were divided into mild (140 cases) and severe group (80 cases) according to PSI scores. Here, we used metagenomic Next Generation Sequencing (mNGS) to detect DNA mainly from bronchoalveolar lavage fluid (BALF) collected from patients to analyze changes in lung microbiome of patients with different disease severity.
Result: We used the mNGS to analyze the pulmonary microecological composition in patients with pulmonary infection. The results of α-diversity and β-diversity analysis showed that the microbial composition between mild and severe groups was similar on the whole. The dominant bacteria were Acinetobacter, Bacillus, Mycobacterium, Staphylococcus, Prevotella, amongst others. LEfse results showed that there were significant differences in virus composition between the mild and severe patients, especially simplexvirus and Cytomegalovirus, which were prominent in the severe group. The random forest model screened 14 kinds of pulmonary infection related pathogens including Corynebacterium, Mycobacterium, Streptococcus, Klebsiella, Acinetobacter, amongst others. In addition, it was found that Rothia was negatively correlated with Acinetobacter, Mycobacterium, Bacillus, Enterococcus and Klebsiella in the mild group through co-occurrence network, while no significant correlation was found in the severe group.
Conclusion: Here, we describe the composition and diversity of the pulmonary microbiome in patients with pulmonary infection. A significant increase in viral replication was found in the severe group, as well as a significant difference in microbial interactions between patients with mild and severe lung infections, particularly the association between the common pathogenic bacteria and Rothia. This suggests that both pathogen co-viral infection and microbial interactions may influence the course of disease. Of course, more research is needed to further explore the specific mechanisms by which microbial interactions influence disease severity.