Guild-Level Microbiome Signature Associated with COVID-19 Severity and Prognosis
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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.
Authors
Guo M, Wu G, Tan Y, Li Y, Jin X, Qi W, Guo X, Zhang C, Zhu Z, Zhao L
Journal
mBio
Year
2023
Keywords:
COVID-19, guild, gut microbiome
Coronavirus disease 2019 (COVID-19) severity has been associated with alterations of the gut microbiota. However, the relationship between gut microbiome alterations and COVID-19 prognosis remains elusive. Here, we performed a genome-resolved metagenomic analysis on fecal samples from 300 in-hospital COVID-19 patients, collected at the time of admission. Among the 2,568 high quality metagenome-assembled genomes (HQMAGs), redundancy analysis identified 33 HQMAGs which showed differential distribution among mild, moderate, and severe/critical severity groups. Co-abundance network analysis determined that the 33 HQMAGs were organized as two competing guilds. Guild 1 harbored more genes for short-chain fatty acid biosynthesis, and fewer genes for virulence and antibiotic resistance, compared with Guild 2. Based on average abundance difference between the two guilds, the guild-level microbiome index (GMI) classified patients from different severity groups (average AUROC [area under the receiver operating curve] = 0.83). Moreover, age-adjusted partial Spearman's correlation showed that GMIs at admission were correlated with 8 clinical parameters, which are predictors for COVID-19 prognosis, on day 7 in hospital. In addition, GMI at admission was associated with death/discharge outcome of the critical patients. We further validated that GMI was able to consistently classify patients with different COVID-19 symptom severities in different countries and differentiated COVID-19 patients from healthy subjects and pneumonia controls in four independent data sets. Thus, this genome-based guild-level signature may facilitate early identification of hospitalized COVID-19 patients with high risk of more severe outcomes at time of admission. IMPORTANCE Previous reports on the associations between COVID-19 and gut microbiome have been constrained by taxonomic-level analysis and overlook the interaction between microbes. By applying a genome-resolved, reference-free, guild-based metagenomic analysis, we demonstrated that the relationship between gut microbiota and COVID-19 is genome-specific instead of taxon-specific or even species-specific. Moreover, the COVID-19-associated genomes were not independent but formed two competing guilds, with Guild 1 potentially beneficial and Guild 2 potentially more detrimental to the host based on comparative genomic analysis. The dominance of Guild 2 over Guild 1 at time of admission was associated with hospitalized COVID-19 patients at high risk for more severe outcomes. Moreover, the guild-level microbiome signature is not only correlated with the symptom severity of COVID-19 patients, but also differentiates COVID-19 patients from pneumonia controls and healthy subjects across different studies. Here, we showed the possibility of using genome-resolved and guild-level microbiome signatures to identify hospitalized COVID-19 patients with a high risk of more severe outcomes at the time of admission.
Experiment 1
Reviewed Marked as Reviewed by Svetlana up on 2024-7-29
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
- Moderate and severe/critical severity
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Mild severity
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- COVID-19 Patients with mild severity symptoms.
- Group 0 sample size Number of subjects in the control (unexposed) group
- 203
- Group 1 sample size Number of subjects in the case (exposed) group
- 88
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
- Dunn's test
- Kruskall-Wallis
- 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)?
- Yes
Signature 1
Reviewed Marked as Reviewed by Svetlana up on 2024-7-29
Source: Fig. 2A
Description: Heatmap of 33 high-quality metagenome-assembled genomes (HQMAGs) identified by redundancy analysis (RDA) and showing differential abundance between the 3 severity groups.
Abundance in Group 1: increased abundance in Mild severity
Revision editor(s): Zheeburg, Aleru Divine
Experiment 2
Reviewed Marked as Reviewed by Svetlana up on 2024-7-29
Differences from previous experiment shown
Subjects
- Group 0 name Corresponds to the control (unexposed) group for case-control studies
- Mild and moderate severity
- Group 1 name Corresponds to the case (exposed) group for case-control studies
- Severe/Critical severity
- Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
- COVID-19 Patients with severe/critical severity symptoms.
- Group 0 sample size Number of subjects in the control (unexposed) group
- 284
- Group 1 sample size Number of subjects in the case (exposed) group
- 12
Lab analysis
Statistical Analysis
Signature 1
Reviewed Marked as Reviewed by Svetlana up on 2024-7-29
Source: Fig. 2A
Description: Heatmap of 33 high-quality metagenome-assembled genomes (HQMAGs) identified by redundancy analysis (RDA) and showing differential abundance between the 3 severity groups.
Abundance in Group 1: increased abundance in Severe/Critical severity
Revision editor(s): Zheeburg, Aleru Divine
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