Integrated gut virome and bacteriome dynamics in COVID-19 patients
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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
Cao J, Wang C, Zhang Y, Lei G, Xu K, Zhao N, Lu J, Meng F, Yu L, Yan J, Bai C, Zhang S, Zhang N, Gong Y, Bi Y, Shi Y, Chen Z, Dai L, Wang J, Yang P
Journal
Gut microbes
Year
2021
Keywords:
COVID-19, bacteriome, dysbiosis, genetic mutation, virome
SARS-CoV-2 is the cause of the current global pandemic of COVID-19; this virus infects multiple organs, such as the lungs and gastrointestinal tract. The microbiome in these organs, including the bacteriome and virome, responds to infection and might also influence disease progression and treatment outcome. In a cohort of 13 COVID-19 patients in Beijing, China, we observed that the gut virome and bacteriome in the COVID-19 patients were notably different from those of five healthy controls. We identified a bacterial dysbiosis signature by observing reduced diversity and viral shifts in patients, and among the patients, the bacterial/viral compositions were different between patients of different severities, although these differences are not entirely distinguishable from the effect of antibiotics. Severe cases of COVID-19 exhibited a greater abundance of opportunistic pathogens but were depleted for butyrate-producing groups of bacteria compared with mild to moderate cases. We replicated our findings in a mouse COVID-19 model, confirmed virome differences and bacteriome dysbiosis due to SARS-CoV-2 infection, and observed that immune/infection-related genes were differentially expressed in gut epithelial cells during infection, possibly explaining the virome and bacteriome dynamics. Our results suggest that the components of the microbiome, including the bacteriome and virome, are affected by SARS-CoV-2 infections, while their compositional signatures could reflect or even contribute to disease severity and recovery processes.
Experiment 1
Reviewed Marked as Reviewed by Atrayees on 2023-7-10
Curated date: 2021/07/02
Curator: Claregrieve1
Revision editor(s): Claregrieve1, WikiWorks, Peace Sandy
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
- Feces Cow dung,Cow pat,Droppings,Dung,Excrement,Excreta,Faeces,Fecal material,Fecal matter,Fewmet,Frass,Guano,Matières fécales@fr,Merde@fr,Ordure,Partie de la merde@fr,Piece of shit,Porción de mierda@es,Portion of dung,Portion of excrement,Portion of faeces,Portion of fecal material,Portion of fecal matter,Portion of feces,Portion of guano,Portion of scat,Portionem cacas,Scat,Spoor,Spraint,Stool,Teil der fäkalien@de,Feces,feces
- 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,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 patients
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Patients with COVID-19
- Group 0 sample size Number of subjects in the control (unexposed) group
- 5
- Group 1 sample size Number of subjects in the case (exposed) group
- 13
Lab analysis
- Sequencing type
- WMS
- 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
- Illumina
Statistical Analysis
- Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
- relative abundances
- Statistical test
- Mann-Whitney (Wilcoxon)
- Significance threshold p-value or FDR threshold used for differential abundance testing (if any)
- 0.05
- MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
- No
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- decreased
Signature 1
Reviewed Marked as Reviewed by Atrayees on 2023-7-10
Source: Figure 3d
Description: Differential abundance in microbial taxa between healthy controls and COVID-19 patients
Abundance in Group 1: increased abundance in COVID-19 patients
Revision editor(s): Claregrieve1
Signature 2
Reviewed Marked as Reviewed by Atrayees on 2023-7-10
Source: Figure 3d
Description: Differential abundance in microbial taxa between healthy controls and COVID-19 patients
Abundance in Group 1: decreased abundance in COVID-19 patients
Revision editor(s): Claregrieve1
Experiment 2
Reviewed Marked as Reviewed by Atrayees on 2023-7-10
Curated date: 2021/07/02
Curator: Claregrieve1
Revision editor(s): Claregrieve1, WikiWorks, Victoria
Differences from previous experiment shown
Subjects
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Antibiotic-naive COVID-19 patients
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Antibiotic-treated COVID-19 patients
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Patients with COVID-19 treated with antibiotics
- Group 0 sample size Number of subjects in the control (unexposed) group
- 8
- Group 1 sample size Number of subjects in the case (exposed) group
- 5
Lab analysis
Statistical Analysis
- Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
- raw counts
- Statistical test
- Linear Regression
Alpha Diversity
- Shannon Estimator of species richness and species evenness: more weight on species richness
- unchanged
Signature 1
Reviewed Marked as Reviewed by Atrayees on 2023-7-10
Source: Figure 3g
Description: Differential abundance of microbial taxa between antibiotic-naive COVID-19 patients and antibiotic-treated COVID-19 patients
Abundance in Group 1: increased abundance in Antibiotic-treated COVID-19 patients
| NCBI | Quality Control | Links |
|---|---|---|
| Veillonella parvula | ||
| unclassified Coprobacillus | ||
| Thomasclavelia ramosa |
Revision editor(s): Claregrieve1
Signature 2
Reviewed Marked as Reviewed by Atrayees on 2023-7-10
Source: Figure 3g
Description: Differential abundance of microbial taxa between antibiotic-naive COVID-19 patients and antibiotic-treated COVID-19 patients
Abundance in Group 1: decreased abundance in Antibiotic-treated COVID-19 patients
Revision editor(s): Claregrieve1
Experiment 3
Reviewed Marked as Reviewed by Atrayees on 2023-7-10
Curated date: 2021/07/02
Curator: Claregrieve1
Revision editor(s): Claregrieve1, WikiWorks, Victoria
Differences from previous experiment shown
Subjects
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Mild COVID-19 patients
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Severe COVID-19 patients
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- Patients with severe COVID-19
- Group 0 sample size Number of subjects in the control (unexposed) group
- 3
- Group 1 sample size Number of subjects in the case (exposed) group
- 3
Lab analysis
Statistical Analysis
- Data transformation Data transformation applied to microbial abundance measurements prior to differential abundance testing (if any).
- relative abundances
- Statistical test
- Mann-Whitney (Wilcoxon)
- MHT correction Have statistical tests be corrected for multiple hypothesis testing (MHT)?
- Yes
Signature 1
Reviewed Marked as Reviewed by Atrayees on 2023-7-10
Source: Table 2
Description: Differential abundance of microbial taxa between mild and severe COVID-19 patients
Abundance in Group 1: increased abundance in Severe COVID-19 patients
Revision editor(s): Claregrieve1
Signature 2
Reviewed Marked as Reviewed by Atrayees on 2023-7-10
Source: Table 2
Description: Differential abundance of microbial taxa between mild and severe COVID-19 patients
Abundance in Group 1: decreased abundance in Severe COVID-19 patients
| NCBI | Quality Control | Links |
|---|---|---|
| Agathobacter rectalis |
Revision editor(s): Claregrieve1
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