Gut colonisation by extended-spectrum β-lactamase-producing Escherichia coli and its association with the gut microbiome and metabolome in Dutch adults: a matched case-control study.


Journal

The Lancet. Microbe
ISSN: 2666-5247
Titre abrégé: Lancet Microbe
Pays: England
ID NLM: 101769019

Informations de publication

Date de publication:
06 2022
Historique:
received: 28 09 2021
revised: 16 12 2021
accepted: 11 02 2022
entrez: 6 6 2022
pubmed: 7 6 2022
medline: 9 6 2022
Statut: ppublish

Résumé

Gut colonisation by extended-spectrum β-lactamase (ESBL)-producing Escherichia coli is a risk factor for developing overt infection. The gut microbiome can provide colonisation resistance against enteropathogens, but it remains unclear whether it confers resistance against ESBL-producing E coli. We aimed to identify a potential role of the microbiome in controlling colonisation by this antibiotic-resistant bacterium. For this matched case-control study, we used faeces from 2751 individuals in a Dutch cross-sectional population study (PIENTER-3) to culture ESBL-producing bacteria. Of these, we selected 49 samples that were positive for an ESBL-producing E coli (ESBL-positive) and negative for several variables known to affect microbiome composition. These samples were matched 1:1 to ESBL-negative samples on the basis of individuals' age, sex, having been abroad or not in the past 6 months, and ethnicity. Shotgun metagenomic sequencing was done and taxonomic species composition and functional annotations (ie, microbial metabolism and carbohydrate-active enzymes) were determined. Targeted quantitative metabolic profiling (proton nuclear magnetic resonance spectroscopy) was done to investigate metabolomic profiles and combinations of univariate (t test and Wilcoxon test), multivariate (principal coordinates analysis, permutational multivariate analysis of variance, and partial least-squares discriminant analysis) and machine-learning approaches (least absolute shrinkage and selection operator and random forests) were used to analyse all the molecular data. No differences in diversity parameters or in relative abundance were observed between ESBL-positive and ESBL-negative groups based on bacterial species-level composition. Machine-learning approaches using microbiota composition did not accurately predict ESBL status (area under the receiver operating characteristic curve [AUROC]=0·41) when using either microbiota composition or any of the functional profiles. The metabolome also did not differ between ESBL groups, as assessed by various methods including random forest (AUROC=0·61). By combining multiomics and machine-learning approaches, we conclude that asymptomatic gut carriage of ESBL-producing E coli is not associated with an altered microbiome composition or function. This finding might suggest that microbiome-mediated colonisation resistance against ESBL-producing E coli is not as relevant as it is against other enteropathogens and antibiotic-resistant bacteria. None.

Sections du résumé

BACKGROUND
Gut colonisation by extended-spectrum β-lactamase (ESBL)-producing Escherichia coli is a risk factor for developing overt infection. The gut microbiome can provide colonisation resistance against enteropathogens, but it remains unclear whether it confers resistance against ESBL-producing E coli. We aimed to identify a potential role of the microbiome in controlling colonisation by this antibiotic-resistant bacterium.
METHODS
For this matched case-control study, we used faeces from 2751 individuals in a Dutch cross-sectional population study (PIENTER-3) to culture ESBL-producing bacteria. Of these, we selected 49 samples that were positive for an ESBL-producing E coli (ESBL-positive) and negative for several variables known to affect microbiome composition. These samples were matched 1:1 to ESBL-negative samples on the basis of individuals' age, sex, having been abroad or not in the past 6 months, and ethnicity. Shotgun metagenomic sequencing was done and taxonomic species composition and functional annotations (ie, microbial metabolism and carbohydrate-active enzymes) were determined. Targeted quantitative metabolic profiling (proton nuclear magnetic resonance spectroscopy) was done to investigate metabolomic profiles and combinations of univariate (t test and Wilcoxon test), multivariate (principal coordinates analysis, permutational multivariate analysis of variance, and partial least-squares discriminant analysis) and machine-learning approaches (least absolute shrinkage and selection operator and random forests) were used to analyse all the molecular data.
FINDINGS
No differences in diversity parameters or in relative abundance were observed between ESBL-positive and ESBL-negative groups based on bacterial species-level composition. Machine-learning approaches using microbiota composition did not accurately predict ESBL status (area under the receiver operating characteristic curve [AUROC]=0·41) when using either microbiota composition or any of the functional profiles. The metabolome also did not differ between ESBL groups, as assessed by various methods including random forest (AUROC=0·61).
INTERPRETATION
By combining multiomics and machine-learning approaches, we conclude that asymptomatic gut carriage of ESBL-producing E coli is not associated with an altered microbiome composition or function. This finding might suggest that microbiome-mediated colonisation resistance against ESBL-producing E coli is not as relevant as it is against other enteropathogens and antibiotic-resistant bacteria.
FUNDING
None.

Identifiants

pubmed: 35659906
pii: S2666-5247(22)00037-4
doi: 10.1016/S2666-5247(22)00037-4
pii:
doi:

Substances chimiques

Anti-Bacterial Agents 0
beta-Lactamases EC 3.5.2.6

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

e443-e451

Commentaires et corrections

Type : CommentIn
Type : CommentIn

Informations de copyright

Copyright © 2022 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of interests EJK is supported by an unrestricted grant from Vedanta Biosciences, has done research for Cubist, Novartis, and Qiagen, and has participated in advisory forums for Astellas, Optimer, Actelion, Pfizer, Sanofi Pasteur, and Seres Therapeutics, all outside of this work. All other authors declare no competing interests. This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Auteurs

Quinten R Ducarmon (QR)

Department of Medical Microbiology, Leiden University Medical Centre, Leiden, Netherlands; Centre for Microbiome Analyses and Therapeutics, Leiden University Medical Centre, Leiden, Netherlands. Electronic address: q.r.ducarmon@lumc.nl.

Romy D Zwittink (RD)

Department of Medical Microbiology, Leiden University Medical Centre, Leiden, Netherlands; Centre for Microbiome Analyses and Therapeutics, Leiden University Medical Centre, Leiden, Netherlands.

Roel P J Willems (RPJ)

Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centres, Amsterdam Medical Centre, Amsterdam Infection and Immunity Institute, Amsterdam, Netherlands.

Aswin Verhoeven (A)

Centre for Proteomics and Metabolomics, Leiden University Medical Centre, Leiden, Netherlands.

Sam Nooij (S)

Department of Medical Microbiology, Leiden University Medical Centre, Leiden, Netherlands; Centre for Microbiome Analyses and Therapeutics, Leiden University Medical Centre, Leiden, Netherlands.

Fiona R M van der Klis (FRM)

Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.

Eelco Franz (E)

Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.

Jolanda Kool (J)

Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.

Martin Giera (M)

Centre for Proteomics and Metabolomics, Leiden University Medical Centre, Leiden, Netherlands.

Christina M J E Vandenbroucke-Grauls (CMJE)

Department of Medical Microbiology and Infection Prevention, Amsterdam University Medical Centres, Amsterdam Medical Centre, Amsterdam Infection and Immunity Institute, Amsterdam, Netherlands.

Susana Fuentes (S)

Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.

Ed J Kuijper (EJ)

Department of Medical Microbiology, Leiden University Medical Centre, Leiden, Netherlands; Centre for Microbiome Analyses and Therapeutics, Leiden University Medical Centre, Leiden, Netherlands; Centre for Infectious Disease Control, National Institute for Public Health and the Environment, Bilthoven, Netherlands.

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