Background Antibiotic resistance is a major global threat. We hypothesised that the chronic obstructive pulmonary disease (COPD) airway is a reservoir of antimicrobial resistance genes (ARGs) that associate with microbiome-specific COPD subgroups.
Objective To determine the resistance gene profiles in respiratory samples from COPD patients and healthy volunteers.
Methods Quantitative PCR targeting 279 specific ARGs was used to profile the resistomes in sputum from subjects with COPD at stable, exacerbation and recovery visits (n=55; COPD-BEAT study), healthy controls with (n=7) or without (n=22) exposure to antibiotics in the preceding 12 months (EXCEED study) and in bronchial brush samples from COPD (n=8) and healthy controls (n=7) (EvA study).
Results ARG mean (SEM) prevalence was greater in stable COPD samples (35.2 (1.6)) than in healthy controls (27.6 (1.7); p=0.004) and correlated with total bacterial abundance (r2=0.23; p<0.001). Prevalence of ARG positive signals in individuals was not related to COPD symptoms, lung function or their changes at exacerbation. In the COPD subgroups designated High γProteobacteria and High Firmicutes, ARG prevalence was not different at stable state but significantly declined from stable through exacerbation to recovery in the former (p=0.011) without changes in total bacterial abundance. The ARG patterns were similar in COPD versus health, COPD microbiome-subgroups and between sputum and bronchoscopic samples independent of antibiotic exposure in the last 12 months.
Conclusions ARGs are highly prevalent in sputum, broadly in proportion to bacterial abundance in both healthy and COPD subjects. Thus, COPD appears to be an ARG reservoir due to high levels of bacterial colonisation.
- COPD exacerbations
- bacterial infection
- infection control
Statistics from Altmetric.com
CB and MRB are joint senior authors.
Contributors MRB, CB and MRO designed the study, MYR and VM delivered the ARG-related laboratory analyses. Samples and analyses and analyses were contributed by KH and MB (BEAT), LG, CJ, NFR and MT (EXCEED), and LZ-H, IG (EvA). RCF was responsible for data management. MYR, CEB, and MRB drafted the manuscript and all authors approved the final version.
Funding This work was funded in part by Airway Disease Predicting Outcomes through Patient Specific Computational Modelling (AirPROM) project (funded through FP7 EU grant), Emphysema versus Airways Disease (EvA FP7; 200506), Wellcome Trust Senior Fellowship (MT), Medical Research Council (COPD-BEAT), National Institute for Health Research (NIHR) Leicester Respiratory Biomedical Centre. This paper presents independent research funded by the NIHR. The views expressed are those of the authors and not necessarily those of the NHS, the NIHR or the Department of Health.
Competing interests None declared.
Patient consent for publication All subjects provided written informed consent.
Ethics approval Ethics approvals were obtained for each study (08/ H0406/189, 13/EM/0226, 08/H0402/19).
Provenance and peer review Not commissioned; externally peer reviewed.
Data availability statement Data are available upon reasonable request. All data relevant to the study are included in the article or uploaded as supplementary information.
If you wish to reuse any or all of this article please use the link below which will take you to the Copyright Clearance Center’s RightsLink service. You will be able to get a quick price and instant permission to reuse the content in many different ways.