Metagenomics Reveals a Core Macrolide Resistome Related to Microbiota in Chronic Respiratory Disease

Study information

Needs review

study design

prospective cohort

Citation

PMID PubMed identifier for scientific articles.

32320621

DOI Digital object identifier for electronic documents.

10.1164/rccm.201911-2202OC

URI

Authors

Mac Aogáin M, Lau KJX, Cai Z, Kumar Narayana J, Purbojati RW, Drautz-Moses DI, Gaultier NE, Jaggi TK, Tiew PY, Ong TH, Siyue Koh M, Lim Yick Hou A, Abisheganaden JA, Tsaneva-Atanasova K, Schuster SC, Chotirmall SH

Journal

American journal of respiratory and critical care medicine

Year

2020

Keywords:

antimicrobial resistance, macrolides, metagenomics, resistome, respiratory disease

Rationale: Long-term antibiotic use for managing chronic respiratory disease is increasing; however, the role of the airway resistome and its relationship to host microbiomes remains unknown.Objectives: To evaluate airway resistomes and relate them to host and environmental microbiomes using ultradeep metagenomic shotgun sequencing.Methods: Airway specimens from 85 individuals with and without chronic respiratory disease (severe asthma, chronic obstructive pulmonary disease, and bronchiectasis) were subjected to metagenomic sequencing to an average depth exceeding 20 million reads. Respiratory and device-associated microbiomes were evaluated on the basis of taxonomical classification and functional annotation including the Comprehensive Antibiotic Resistance Database to determine airway resistomes. Co-occurrence networks of gene-microbe association were constructed to determine potential microbial sources of the airway resistome. Paired patient-inhaler metagenomes were compared (n = 31) to assess for the presence of airway-environment overlap in microbiomes and/or resistomes.Measurements and Main Results: Airway metagenomes exhibit taxonomic and metabolic diversity and distinct antimicrobial resistance patterns. A "core" airway resistome dominated by macrolide but with high prevalence of β-lactam, fluoroquinolone, and tetracycline resistance genes exists and is independent of disease status or antibiotic exposure. Streptococcus and Actinomyces are key potential microbial reservoirs of macrolide resistance including the ermX, ermF, and msrD genes. Significant patient-inhaler overlap in airway microbiomes and their resistomes is identified where the latter may be a proxy for airway microbiome assessment in chronic respiratory disease.Conclusions: Metagenomic analysis of the airway reveals a core macrolide resistome harbored by the host microbiome.

Experiment 1

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Curated date: 2023/10/22

Curator: ChiomaBlessing

Revision editor(s): WikiWorks, Peace Sandy, ChiomaBlessing, KateRasheed

Subjects

Location of subjects: Singapore

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: Sputum

Condition The experimental condition / phenotype studied according to the Experimental Factor Ontology

Group 0 name Corresponds to the control (unexposed) group for case-control studies: Non-diseased/ healthy individuals (ND)

Group 1 name Corresponds to the case (exposed) group for case-control studies: Diseased individuals (D)

Group 1 definition Diagnostic criteria applied to define the specific condition / phenotype represented in the case (exposed) group: Patients with a range of chronic respiratory disease states (severe asthma, chronic obstructive pulmonary disease- COPD, and bronchiectasis)

Group 0 sample size Number of subjects in the control (unexposed) group: 13

Group 1 sample size Number of subjects in the case (exposed) group: 41

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: 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)?: No

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: increased

Chao1 Abundance-based estimator of species richness: decreased

Simpson Estimator of species richness and species evenness: more weight on species evenness: unchanged

Signature 1

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Curated date: 2023/10/22

Curator: ChiomaBlessing

Revision editor(s): ChiomaBlessing, WikiWorks

Source: Supplemental. fig. E3D and Supplemental fig. E3E

Description: Differential microbial abundance between diseased (D) and nondiseased (ND)/ healthy individuals

Abundance in Group 1: increased abundance in Diseased individuals (D)

NCBI	Quality Control	Links
Arachnia
Bifidobacterium
Corynebacterium
Escherichia
Haemophilus
Klebsiella
Paenibacillus
Pseudomonas
Psychrobacter
Tannerella
Rothia mucilaginosa

Revision editor(s): ChiomaBlessing, WikiWorks

Signature 2

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Your review change was submitted

Needs review

Curated date: 2023/10/22

Curator: ChiomaBlessing

Revision editor(s): ChiomaBlessing, WikiWorks

Source: Supplemental. fig. E3D and Supplemental fig. E3E

Description: Differential microbial abundance between diseased (D) and nondiseased (ND)/ healthy individuals

Abundance in Group 1: decreased abundance in Diseased individuals (D)

NCBI	Quality Control	Links
Parvimonas
Mycoplasma
Selenomonas
Dialister
Leptotrichia
Mogibacterium
Atopobium
Aggregatibacter
Solobacterium
Olsenella
Catonella
Lautropia
Actinobaculum
Campylobacter
Lachnoanaerobaculum
Peptostreptococcus
Alloprevotella
Clostridium
Desulfomicrobium
Fusobacterium
Treponema
Prevotella

Revision editor(s): ChiomaBlessing, WikiWorks