Alterations in Gut Microbiota of Patients With COVID-19 During Time of Hospitalization

From BugSigDB
Reviewed Marked as Reviewed by Chloe on 11 August 2021
study design
case-control
Citation
PMID
URI
Authors
Zuo T, Zhang F, Lui GCY, Yeoh YK, Li AYL, Zhan H, Wan Y, Chung ACK, Cheung CP, Chen N, Lai CKC, Chen Z, Tso EYK, Fung KSC, Chan V, Ling L, Joynt G, Hui DSC, Chan FKL, Chan PKS, Ng SC
Journal
Gastroenterology
Year
2020
BACKGROUND & AIMS: Although severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects gastrointestinal tissues, little is known about the roles of gut commensal microbes in susceptibility to and severity of infection. We investigated changes in fecal microbiomes of patients with SARS-CoV-2 infection during hospitalization and associations with severity and fecal shedding of virus. METHODS: We performed shotgun metagenomic sequencing analyses of fecal samples from 15 patients with Coronavirus Disease 2019 (COVID-19) in Hong Kong, from February 5 through March 17, 2020. Fecal samples were collected 2 or 3 times per week from time of hospitalization until discharge; disease was categorized as mild (no radiographic evidence of pneumonia), moderate (pneumonia was present), severe (respiratory rate ≥30/min, or oxygen saturation ≤93% when breathing ambient air), or critical (respiratory failure requiring mechanical ventilation, shock, or organ failure requiring intensive care). We compared microbiome data with those from 6 subjects with community-acquired pneumonia and 15 healthy individuals (controls). We assessed gut microbiome profiles in association with disease severity and changes in fecal shedding of SARS-CoV-2. RESULTS: Patients with COVID-19 had significant alterations in fecal microbiomes compared with controls, characterized by enrichment of opportunistic pathogens and depletion of beneficial commensals, at time of hospitalization and at all timepoints during hospitalization. Depleted symbionts and gut dysbiosis persisted even after clearance of SARS-CoV-2 (determined from throat swabs) and resolution of respiratory symptoms. The baseline abundance of Coprobacillus, Clostridium ramosum, and Clostridium hathewayi correlated with COVID-19 severity; there was an inverse correlation between abundance of Faecalibacterium prausnitzii (an anti-inflammatory bacterium) and disease severity. Over the course of hospitalization, Bacteroides dorei, Bacteroides thetaiotaomicron, Bacteroides massiliensis, and Bacteroides ovatus, which downregulate expression of angiotensin-converting enzyme 2 (ACE2) in murine gut, correlated inversely with SARS-CoV-2 load in fecal samples from patients. CONCLUSIONS: In a pilot study of 15 patients with COVID-19, we found persistent alterations in the fecal microbiome during the time of hospitalization, compared with controls. Fecal microbiota alterations were associated with fecal levels of SARS-CoV-2 and COVID-19 severity. Strategies to alter the intestinal microbiota might reduce disease severity.

Experiment 1


Reviewed Marked as Reviewed by Chloe on 11 August 2021

Curated date: 2021/07/02

Curator: Claregrieve1

Revision editor(s): WikiWorks753, Chloe, Claregrieve1

Subjects

Location of subjects Country from which study subjects were recruited
China
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
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
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
Uninfected controls, pneumonia patients, antibiotics treated COVID-19 patients
Group 1 name Corresponds to the case (exposed) group for case-control studies
Antibiotic-naive COVID-19 patients
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
COVID-19 patients hospitalized with SARS-CoV-2 infection confirmed by 2 consecutive RT-PCR tests, not treated with antibiotics
Group 0 sample size Number of subjects in the control (unexposed) group
29
Group 1 sample size Number of subjects in the case (exposed) group
7

Lab analysis

Sequencing type Experimental technique used for quantifying microbial abundance
WMS
Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
Illumina

Statistical Analysis

Statistical test Statistical test or computational tool used for differential abundance testing
Linear Regression
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


Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment
age, antibiotic exposure, comorbidity, sex


Signature 1

Reviewed Marked as Reviewed by Chloe on 11 August 2021

Curated date: 2021/07/02

Curator: Claregrieve1

Revision editor(s): Claregrieve1

Source: Table 2

Description: Differential abundance of microbial taxa between antibiotic-naive COVID-19 patients and healthy controls

Abundance in Group 1: increased abundance in Antibiotic-naive COVID-19 patients

NCBI Links
Actinomyces viscosus
Clostridium hathewayi CAG:224
Bacteroides nordii

Revision editor(s): Claregrieve1

Signature 2

Reviewed Marked as Reviewed by Chloe on 11 August 2021

Curated date: 2021/08/11

Curator: Chloe

Revision editor(s): Chloe

Source: Table 2

Description: Differential abundance of microbial taxa between antibiotic-naive COVID-19 patients and healthy controls

Abundance in Group 1: decreased abundance in Antibiotic-naive COVID-19 patients

NCBI Links
Eubacterium ventriosum

Revision editor(s): Chloe

Experiment 2


Reviewed Marked as Reviewed by Chloe on 11 August 2021

Curated date: 2021/07/02

Curator: Claregrieve1

Revision editor(s): WikiWorks753, Chloe, Claregrieve1

Subjects

Location of subjects Country from which study subjects were recruited
China
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
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
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
Antibiotic-naive COVID-19 patients, pneumonia patients, uninfected controls
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
COVID-19 patients hospitalized with SARS-CoV-2 infection confirmed by 2 consecutive RT-PCR tests, treated with antibiotics
Group 0 sample size Number of subjects in the control (unexposed) group
28
Group 1 sample size Number of subjects in the case (exposed) group
8

Lab analysis

Sequencing type Experimental technique used for quantifying microbial abundance
WMS
Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
Illumina

Statistical Analysis

Statistical test Statistical test or computational tool used for differential abundance testing
Linear Regression
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


Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment
age, antibiotic exposure, comorbidity, sex


Signature 1

Reviewed Marked as Reviewed by Chloe on 11 August 2021

Curated date: 2021/07/02

Curator: Claregrieve1

Revision editor(s): Claregrieve1

Source: Table 2

Description: Differential abundance of microbial taxa between antibiotic-naive and antibiotic-treated COVID-19 patients

Abundance in Group 1: decreased abundance in Antibiotic-treated COVID-19 patients

NCBI Links
Dorea formicigenerans
Blautia
Faecalibacterium
Faecalibacterium prausnitzii
Eubacteriaceae
Eubacterium
Eubacterium rectale CAG:36
Oscillospiraceae
Roseburia
Coprococcus
Ruminococcus obeum CAG:39
Lachnospiraceae bacterium 5_1_63FAA
Eubacterium ventriosum

Revision editor(s): Claregrieve1

Experiment 3


Reviewed Marked as Reviewed by Chloe on 11 August 2021

Curated date: 2021/07/02

Curator: Claregrieve1

Revision editor(s): WikiWorks753, Chloe, Claregrieve1

Subjects

Location of subjects Country from which study subjects were recruited
China
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
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
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
Uninfected controls, COVID-19 patients
Group 1 name Corresponds to the case (exposed) group for case-control studies
Pneumonia controls
Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group
Patients hospitalized with community-acquired pneumonia
Group 0 sample size Number of subjects in the control (unexposed) group
30
Group 1 sample size Number of subjects in the case (exposed) group
6

Lab analysis

Sequencing type Experimental technique used for quantifying microbial abundance
WMS
Sequencing platform Manufacturer and experimental platform used for quantifying microbial abundance
Illumina

Statistical Analysis

Statistical test Statistical test or computational tool used for differential abundance testing
Linear Regression
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


Confounders controlled for Confounding factors that have been accounted for by stratification or model adjustment
age, antibiotic exposure, comorbidity, sex


Signature 1

Reviewed Marked as Reviewed by Chloe on 11 August 2021

Curated date: 2021/07/02

Curator: Claregrieve1

Revision editor(s): Chloe, Claregrieve1

Source: Table 2

Description: Differential abundance of microbial taxa between healthy controls and pneumonia controls

Abundance in Group 1: decreased abundance in Pneumonia controls

NCBI Links
Coprobacillus
Enterococcus faecium
Erysipelatoclostridium ramosum
Lachnospiraceae bacterium 5_1_63FAA
Eubacterium ventriosum

Revision editor(s): Chloe, Claregrieve1