The active lung microbiota landscape of COVID-19 patients through the metatranscriptome data analysis
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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
Han Y, Jia Z, Shi J, Wang W, He K
Journal
BioImpacts : BI
Year
2022
Introduction: With the outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the interaction between the host and SARS-CoV-2 was widely studied. However, it is unclear whether and how SARS-CoV-2 infection affects lung microflora, which contribute to COVID-19 complications. Methods: Here, we analyzed the metatranscriptomic data of bronchoalveolar lavage fluid (BALF) of 19 COVID-19 patients and 23 healthy controls from 6 independent projects and detailed the active microbiota landscape in both healthy individuals and COVID-19 patients. Results: The infection of SARS-CoV-2 could deeply change the lung microbiota, evidenced by the α-diversity, β-diversity, and species composition analysis based on bacterial microbiota and virome. Pathogens (e.g., Klebsiella oxytoca causing pneumonia as well), immunomodulatory probiotics (e.g., lactic acid bacteria and Faecalibacterium prausnitzii, a butyrate producer), and Tobacco mosaic virus (TMV) were enriched in the COVID-19 group, suggesting a severe microbiota dysbiosis. The significant correlation between Rothia mucilaginosa, TMV, and SARS-CoV-2 revealed drastic inflammatory battles between the host, SARS-CoV-2, and other microbes in the lungs. Notably, TMV only existed in the COVID-19 group, while human respirovirus 3 (HRV 3) only existed in the healthy group. Our study provides insights into the active microbiota in the lungs of COVID-19 patients and would contribute to the understanding of the infection mechanism of SARS-CoV-2 and the treatment of the disease and complications. Conclusion: SARS-COV-2 infection deeply altered the lung microbiota of COVID-19 patients. The enrichment of several other pathogens, immunomodulatory probiotics (lactic acid or butyrate producers), and TMV in the COVID-19 group suggests a complex and active lung microbiota disorder.
Experiment 1
Needs review
Subjects
- Location of subjects
- China
- Switzerland
- Host species Species from which microbiome was sampled (if applicable)
- Homo sapiens
- Body site Anatomical site where microbial samples were extracted from according to the Uber Anatomy Ontology
- Lung Pulmo,Lung
- Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology
- COVID-19 2019 novel coronavirus,2019 novel coronavirus infection,2019-nCoV,2019-nCoV infection,beta-CoV,beta-CoVs,betacoronavirus,coronavirus disease 2019,SARS-coronavirus 2,SARS-CoV-2,severe acute respiratory syndrome coronavirus 2,severe acute respiratory syndrome coronavirus 2 infectious disease,β-coronavirus,β-CoV,β-CoVs,COVID-19
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Healthy controls
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- COVID-19 cases
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- COVID-19 infected patients
- Group 0 sample size Number of subjects in the control (unexposed) group
- 23
- Group 1 sample size Number of subjects in the case (exposed) group
- 19
Lab analysis
- Sequencing type
- WMS
- Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
- Sequencing platform: "IDseq" is not in the list (DNA-DNA Hybridization, Human Intestinal Tract Chip, Illumina, Ion Torrent, Non-quantitative PCR, PacBio RS, PhyloChip, Roche454, RT-qPCR, Mass spectrometry, ...) of allowed values.IDseq
Statistical Analysis
- Statistical test
- DESeq2
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 1e-11
- MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
- Yes
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- increased
Signature 1
Needs review
Source: Supplementary Table 2
Description: Differential microbial abundance between COVID-19 patients and healthy controls
Abundance in Group 1: increased abundance in COVID-19 cases
Revision editor(s): Claregrieve1
Signature 2
Needs review
Source: Supplementary Table 2
Description: Differential microbial abundance between COVID-19 patients and healthy controls
Abundance in Group 1: decreased abundance in COVID-19 cases
| NCBI | Links |
|---|---|
| Campylobacter gracilis | |
| Campylobacter rectus | |
| Campylobacter showae | |
| Treponema putidum |
Revision editor(s): Claregrieve1
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