The lower respiratory tract microbiome of critically ill patients with COVID-19
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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
Gaibani P, Viciani E, Bartoletti M, Lewis RE, Tonetti T, Lombardo D, Castagnetti A, Bovo F, Horna CS, Ranieri M, Viale P, Re MC, Ambretti S
Journal
Scientific reports
Year
2021
COVID-19 infection may predispose to secondary bacterial infection which is associated with poor clinical outcome especially among critically ill patients. We aimed to characterize the lower respiratory tract bacterial microbiome of COVID-19 critically ill patients in comparison to COVID-19-negative patients. We performed a 16S rRNA profiling on bronchoalveolar lavage (BAL) samples collected between April and May 2020 from 24 COVID-19 critically ill subjects and 24 patients with non-COVID-19 pneumonia. Lung microbiome of critically ill patients with COVID-19 was characterized by a different bacterial diversity (PERMANOVA on weighted and unweighted UniFrac Pr(> F) = 0.001) compared to COVID-19-negative patients with pneumonia. Pseudomonas alcaligenes, Clostridium hiranonis, Acinetobacter schindleri, Sphingobacterium spp., Acinetobacter spp. and Enterobacteriaceae, characterized lung microbiome of COVID-19 critically ill patients (LDA score > 2), while COVID-19-negative patients showed a higher abundance of lung commensal bacteria (Haemophilus influenzae, Veillonella dispar, Granulicatella spp., Porphyromonas spp., and Streptococcus spp.). The incidence rate (IR) of infections during COVID-19 pandemic showed a significant increase of carbapenem-resistant Acinetobacter baumannii (CR-Ab) infection. In conclusion, SARS-CoV-2 infection and antibiotic pressure may predispose critically ill patients to bacterial superinfection due to opportunistic multidrug resistant pathogens.
Experiment 1
Needs review
Curated date: 2021/07/14
Curator: Claregrieve1
Revision editor(s): Claregrieve1, WikiWorks, Peace Sandy
Subjects
- Location of subjects
- Italy
- 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
- 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
- Non-COVID-19 pneumonia patients
- 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 positive for SARS-CoV-2 by RT-PCR on nasopharyngeal swabs or lower respiratory tract samples
- Group 0 sample size Number of subjects in the control (unexposed) group
- 24
- Group 1 sample size Number of subjects in the case (exposed) group
- 24
Lab analysis
- Sequencing type
- 16S
- 16S variable region One or more hypervariable region(s) of the bacterial 16S gene
- V3-V4
- 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
- LEfSe
- 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
- 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
- Chao1 Abundance-based estimator of species richness
- unchanged
- Inverse Simpson Modification of Simpsons index D as 1/D to obtain high values in datasets of high diversity and vice versa
- unchanged
- Richness Number of species
- unchanged
Signature 1
Needs review
Source: Figure 3
Description: Differential microbial abundance between COVID-19 positive patients and non-COVID pneumonia patients by LEfSe
Abundance in Group 1: increased abundance in COVID-19 patients
| NCBI | Quality Control | Links |
|---|---|---|
| Enterobacteriaceae | ||
| Acinetobacter | ||
| Acinetobacter schindleri | ||
| Sphingobacterium | ||
| Peptacetobacter hiranonis | ||
| Pseudomonas alcaligenes |
Revision editor(s): Claregrieve1
Signature 2
Needs review
Source: Figure 3
Description: Differential microbial abundance between COVID-19 positive patients and non-COVID pneumonia patients by LEfSe
Abundance in Group 1: decreased abundance in COVID-19 patients
Revision editor(s): Claregrieve1, Aleru002
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