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

Abstract

BackgroundLung infection is a global health problem associated with high morbidity and 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.MethodPatients with pulmonary infection or suspected infection were divided into the mild group (140 cases) and the severe group (80 cases) according to pneomonia severity index (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 the lung microbiome of patients with different disease severity.ResultWe used the mNGS to analyze the pulmonary microecological composition in patients with pulmonary infection. The results of alpha diversity and beta 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, and Prevotella, among others. Linear discriminant analysis effect size (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, and Acinetobacter. 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.ConclusionHere, 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.

Microbiota and Immunity during Respiratory Infections: Lung and Gut Affair

“…In the disease condition, the presence and abundance of pathogens in the lung are not consistently mirrored in the oropharynx, underlining the importance of direct sampling of the lower airway with bronchoalveolar lavage (BALF) in investigating lung microbiota [23]. Several studies comparing diseased versus healthy lungs found significant differences in community composition, with the disease condition being associated with loss of bacteria diversity or with a dominance of a single taxon or small group of taxa [24][25][26]. Microbial dysbiosis characterizes various lung diseases, in which a reduced microbial diversity has been also associated with disease progression [7,[27][28][29].…”

“…A recent work describes a significant increased viral replication in severe pulmonary infections, and a difference in microbial interactions between patients with bland and severe disease, especially the association between the common pathogenic bacteria and Rothia [26]. The high mortality risk due to influenza is mostly attributed to secondary bacterial infections.…”

Deciphering the microbial landscape of lower respiratory tract infections: insights from metagenomics and machine learning

“…The lung microbiota plays a vital role in maintaining respiratory health and influencing the severity of lower respiratory tract diseases ( Fenn et al., 2022 ). Although studies have explored the characteristics of lung microbiota across different severity levels of lung infections using metagenomics ( Zhan et al., 2023 ), multidimensional analysis of lung microbiota characteristics remains limited.…”