Characteristics of the pulmonary microbiota in patients with mild and severe pulmonary infection
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Study information
-
Quality control
- Retracted paper
- Contamination issues suspected
- Batch effect issues suspected
- Uncontrolled confounding suspected
- Results are suspect (various reasons)
- Tags applied
study design
Citation
PMID PubMed identifier for scientific articles.
DOI Digital object identifier for electronic documents.
URI Uniform resource identifier for web resources.
Authors
Zhan D, Li D, Yuan K, Sun Y, He L, Zhong J, Wang L
Journal
Frontiers in cellular and infection microbiology
Year
2023
Keywords:
pulmonary infection, biomarker, network, pulmonary microbiota, severity
BACKGROUND: Lung 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. METHOD: Patients 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. RESULT: We 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. 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.
Experiment 1
Subjects
- Location of subjects
- China
- Host species Species from which microbiome was sampled. Contact us to have more species added.
- Homo sapiens
- Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
- Sputum Expectoration,Sputum,sputum
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- Lung disease DIS PULM,disease of lung,disease or disorder of lung,Disease, Lung,Disease, Pulmonary,Diseases, Lung,Diseases, Pulmonary,disorder of lung,LUNG DIS,lung disease,lung disease or disorder,Lung Diseases,lung disorder,lung disorders,PULM DIS,Pulmonary Disease,pulmonary disease,Pulmonary Diseases,pulmonary diseases,pulmonary disorder,pulmonary disorders,Lung disease
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- mild group
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- severe group
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Patients who were at least 18 years of age with pulmonary infection.
- Group 0 sample size Number of subjects in the control (unexposed) group
- 140
- Group 1 sample size Number of subjects in the case (exposed) group
- 80
Lab analysis
- Sequencing type
- PCR
- 16S variable region One or more hypervariable region(s) of the bacterial 16S gene
- Not specified
- Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
- MGISEQ-2000
Statistical Analysis
- Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
- relative abundances
- Statistical test
- LEfSe
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 0.05
- LDA Score above Threshold for the linear discriminant analysis (LDA) score for studies using the popular LEfSe tool
- 2
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- unchanged
- Simpson Estimator of species richness and species evenness: more weight on species evenness
- unchanged
Signature 1
Source: Figure 4A
Description: Bacterial biomarkers were identified by linear discriminant analysis effect size (LEfSe) algorithm. (A) Bacterial histograms of unique biomarkers based on LEfSe (>2). The length of the bar chart represents the magnitude of the impact of significantly different genus.
Abundance in Group 1: increased abundance in severe group
Revision editor(s): Nuerteye
Signature 2
Source: Figure 4A
Description: Bacterial biomarkers were identified by linear discriminant analysis effect size (LEfSe) algorithm. (A) Bacterial histograms of unique biomarkers based on LEfSe (>2). The length of the bar chart represents the magnitude of the impact of significantly different genus.
Abundance in Group 1: decreased abundance in severe group
| NCBI | Quality Control | Links |
|---|---|---|
| Cloacibacterium | ||
| MariprofundusMariprofundus | ||
| Paraburkholderia | ||
| Mesorhizobium | ||
| Photobacterium | ||
| Cronobacter | ||
| ToxoplasmaToxoplasma | ||
| Mycobacterium |
Revision editor(s): Nuerteye
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