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
Authors
Han Y, Jia Z, Shi J, Wang W, He K
Journal
BioImpacts : BI
Year
2022
Keywords:
COVID-19, Faecalibacterium prausnitzii, Lactic acid bacteria, Microbiota, SARS-CoV-2
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 | Quality Control | Links |
|---|---|---|
| Campylobacter gracilis | ||
| Campylobacter rectus | ||
| Campylobacter showae | ||
| Treponema putidum |
Revision editor(s): Claregrieve1
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