Relationship between inflammatory status and microbial composition in severe asthma and during exacerbation.

BACKGROUND: In T2-mediated severe asthma, biologic therapies, such as mepolizumab, are increasingly used to control disease. Current biomarkers can indicate adequate suppression of T2 inflammation, but it is unclear whether they provide information about airway microbial composition. We investigated the relationships between current T2 biomarkers and microbial profiles, characteristics associated with a ProteobacteriaHIGH microbial profile and the effects of mepolizumab on airway ecology. METHODS: Microbiota sequencing was performed on sputum samples obtained at stable and exacerbation state from 140 subjects with severe asthma participating in two clinical trials. Inflammatory subgroups were compared on the basis of biomarkers, including FeNO and sputum and blood eosinophils. ProteobacteriaHIGH subjects were identified by Proteobacteria to Firmicutes ratio ≥0.485. Where paired sputum from stable visits was available, we compared microbial composition at baseline and following ≥12 weeks of mepolizumab. RESULTS: Microbial composition was not related to inflammatory subgroup based on sputum or blood eosinophils. FeNO ≥50 ppb when stable and at exacerbation indicated a group with less dispersed microbial profiles characterised by high alpha-diversity and low Proteobacteria. ProteobacteriaHIGH subjects were neutrophilic and had a longer time from asthma diagnosis than ProteobacteriaLOW subjects. In those studied, mepolizumab did not alter airway bacterial load or lead to increased Proteobacteria. CONCLUSION: High FeNO could indicate a subgroup of severe asthma less likely to benefit from antimicrobial strategies at exacerbation or in the context of poor control. Where FeNO is <50 ppb, biomarkers of microbial composition are required to identify those likely to respond to microbiome-directed strategies. We found no evidence that mepolizumab alters airway microbial composition.

Inflammatory Endotype-associated Airway Microbiome in Chronic Obstructive Pulmonary Disease Clinical Stability and Exacerbations: A Multicohort Longitudinal Analysis.

Rationale: Understanding the role of the airway microbiome in chronic obstructive pulmonary disease (COPD) inflammatory endotypes may help to develop microbiome-based diagnostic and therapeutic approaches. Objectives: To understand the association of the airway microbiome with neutrophilic and eosinophilic COPD at stability and during exacerbations. Methods: An integrative analysis was performed on 1,706 sputum samples collected longitudinally from 510 patients with COPD recruited at four UK sites of the BEAT-COPD (Biomarkers to Target Antibiotic and Systemic COPD), COPDMAP (Chronic Obstructive Pulmonary Disease Medical Research Council/Association of the British Pharmaceutical Industry), and AERIS (Acute Exacerbation and Respiratory Infections in COPD) cohorts. The microbiome was analyzed using COPDMAP and AERIS as a discovery data set and BEAT-COPD as a validation data set. Measurements and Main Results: The airway microbiome in neutrophilic COPD was heterogeneous, with two primary community types differentiated by the predominance of Haemophilus. The Haemophilus-predominant subgroup had elevated sputum IL-1ß and TNFα (tumor necrosis factor α) and was relatively stable over time. The other neutrophilic subgroup with a balanced microbiome profile had elevated sputum and serum IL-17A and was temporally dynamic. Patients in this state at stability were susceptible to the greatest microbiome shifts during exacerbations. This subgroup can temporally switch to both neutrophilic Haemophilus-predominant and eosinophilic states that were otherwise mutually exclusive. Time-series analysis on the microbiome showed that the temporal trajectories of Campylobacter and Granulicatella were indicative of intrapatient switches from neutrophilic to eosinophilic inflammation, in track with patient sputum eosinophilia over time. Network analysis revealed distinct host-microbiome interaction patterns among neutrophilic Haemophilus-predominant, neutrophilic balanced microbiome, and eosinophilic subgroups. Conclusions: The airway microbiome can stratify neutrophilic COPD into subgroups that justify different therapies. Neutrophilic and eosinophilic COPD are interchangeable in some patients. Monitoring temporal variability of the airway microbiome may track patient inflammatory status over time.

Resistome analyses of sputum from COPD and healthy subjects reveals bacterial load-related prevalence of target genes.

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.

The sputum microbiome is distinct between COPD and health, independent of smoking history.

BACKGROUND: Airway bacterial dysbiosis is a feature of chronic obstructive pulmonary disease (COPD). However, there is limited comparative data of the lung microbiome between healthy smokers, non-smokers and COPD. METHODS: We compared the 16S rRNA gene-based sputum microbiome generated from pair-ended Illumina sequencing of 124 healthy subjects (28 smokers and 96 non-smokers with normal lung function), with single stable samples from 218 COPD subjects collected from three UK clinical centres as part of the COPDMAP consortium. RESULTS: In healthy subjects Firmicutes, Bacteroidetes and Actinobacteria were the major phyla constituting 88% of the total reads, and Streptococcus, Veillonella, Prevotella, Actinomyces and Rothia were the dominant genera. Haemophilus formed only 3% of the healthy microbiome. In contrast, Proteobacteria was the most dominant phylum accounting for 50% of the microbiome in COPD subjects, with Haemophilus and Moraxella at genus level contributing 25 and 3% respectively. There were no differences in the microbiome profile within healthy and COPD subgroups when stratified based on smoking history. Principal coordinate analysis on operational taxonomic units showed two distinct clusters, representative of healthy and COPD subjects (PERMANOVA, p = 0·001). CONCLUSION: The healthy and COPD sputum microbiomes are distinct and independent of smoking history. Our results underline the important role for Gammaproteobacteria in COPD.

Lung microbiome dynamics in COPD exacerbations.

Increasing evidence suggests that the lung microbiome plays an important role in chronic obstructive pulmonary disease (COPD) severity. However, the dynamics of the lung microbiome during COPD exacerbations and its potential role in disease aetiology remain poorly understood.We completed a longitudinal 16S ribosomal RNA survey of the lung microbiome on 476 sputum samples collected from 87 subjects with COPD at four visits defined as stable state, exacerbation, 2 weeks post-therapy and 6 weeks recovery.Our analysis revealed a dynamic lung microbiota where changes appeared to be associated with exacerbation events and indicative of specific exacerbation phenotypes. Antibiotic and steroid treatments appear to have differential effects on the lung microbiome. We depict a microbial interaction network for the lung microbiome and suggest that perturbation of a few bacterial operational taxonomic units, in particular Haemophilus spp., could greatly impact the overall microbial community structure. Furthermore, several serum and sputum biomarkers, in particular sputum interleukin-8, appear to be highly correlated with the structure and diversity of the microbiome.Our study furthers the understanding of lung microbiome dynamics in COPD patients and highlights its potential as a biomarker, and possibly a target, for future respiratory therapeutics.

Lung microbiome composition and bronchial epithelial gene expression in patients with COPD versus healthy individuals: a bacterial 16S rRNA gene sequencing and host transcriptomic analysis.

BACKGROUND: Chronic obstructive pulmonary disease (COPD) is associated with airway inflammation and bacterial dysbiosis. The relationship between the airway microbiome and bronchial gene expression in COPD is poorly understood. We aimed to identify differences in the airway microbiome from bronchial brushings in patients with COPD and healthy individuals and to investigate whether any distinguishing bacteria are related to bronchial gene expression. METHODS: For this 16S rRNA gene sequencing and host transcriptomic analysis, individuals aged 45-75 years with mild-to-moderate COPD either receiving or not receiving inhaled corticosteroids and healthy individuals in the same age group were recruited as part of the Emphysema versus Airways Disease (EvA) consortium from nine centres in the UK, Germany, Italy, Poland, and Hungary. Individuals underwent clinical characterisation, spirometry, CT scans, and bronchoscopy. From bronchoscopic bronchial brush samples, we obtained the microbial profiles using 16S rRNA gene sequencing and gene expression using the RNA-Seq technique. We analysed bacterial genera relative abundance and the associations between genus abundance and clinical characteristics or between genus abundance and host lung transcriptional signals in patients with COPD versus healthy individuals, and in patients with COPD with versus without inhaled corticosteroids treatment. FINDINGS: Between February, 2009, and March, 2012, we obtained brush samples from 574 individuals. We used 546 of 574 samples for analysis, including 207 from healthy individuals and 339 from patients with COPD (192 with inhaled corticosteroids and 147 without). The bacterial genera that most strongly distinguished patients with COPD from healthy individuals were Prevotella (median relative abundance 33·5%, IQR 14·5-49·4, in patients with COPD vs 47·7%, 31·1-60·7, in healthy individuals; p<0·0001), Streptococcus (8·6%, 3·8-15·8, vs 5·3%, 3·0-10·1; p<0·0001), and Moraxella (0·05%, 0·02-0·14, vs 0·02%, 0-0·07; p<0·0001). Prevotella abundance was inversely related to COPD severity in terms of symptoms and positively related to lung function and exercise capacity. 446 samples had assessable RNA-seq data, 257 from patients with COPD (136 with inhaled corticosteroids and 121 without) and 189 from healthy individuals. No significant associations were observed between lung transcriptional signals from bronchial brushings and abundance of bacterial genera in patients with COPD without inhaled corticosteroids treatment and in healthy individuals. In patients with COPD treated with inhaled corticosteroids, Prevotella abundance was positively associated with expression of epithelial genes involved in tight junction promotion and Moraxella abundance was associated with expression of the IL-17 and TNF inflammatory pathways. INTERPRETATION: With increasing severity of COPD, the airway microbiome is associated with decreased abundance of Prevotella and increased abundance of Moraxella in concert with downregulation of genes promoting epithelial defence and upregulation of pro-inflammatory genes associated with inhaled corticosteroids use. Our work provides further insight in understanding the relationship between microbiome alteration and host inflammatory response, which might lead to novel therapeutic strategies for COPD. FUNDING: EU Seventh Framework Programme, National Institute for Health Research.

Sputum Streptococcus pneumoniae is reduced in COPD following treatment with benralizumab.

We hypothesized whether the reduction in eosinophilic airway inflammation in patients with chronic obstructive pulmonary disease (COPD) following treatment with benralizumab, a humanized, afucosylated, monoclonal antibody that binds to interleukin-5 receptor α, increases the airway bacterial load. Analysis of sputum samples of COPD patients participating in a Phase II trial of benralizumab indicated that sputum 16S rDNA load and Streptococcus pneumoniae were reduced following treatment with benralizumab. However, in vitro, eosinophils did not affect the killing of the common airway pathogens S. pneumoniae or Haemophilus influenzae. Thus, benralizumab may have an indirect effect upon airway bacterial load.

Microbiome balance in sputum determined by PCR stratifies COPD exacerbations and shows potential for selective use of antibiotics.

BACKGROUND: While a subgroup of patients with exacerbations of chronic obstructive pulmonary disease (COPD) clearly benefit from antibiotics, their identification remains challenging. We hypothesised that selective assessment of the balance between the two dominant bacterial groups (Gammaproteobacteria (G) and Firmicutes (F)) in COPD sputum samples might reveal a subgroup with a bacterial community structure change at exacerbation that was restored to baseline on recovery and potentially reflects effective antibiotic treatment. METHODS: Phylogenetically specific 16S rRNA genes were determined by quantitative real time PCR to derive a G:F ratio in serial sputum samples from 66 extensively-phenotyped COPD exacerbation episodes. RESULTS: Cluster analysis based on Euclidean distance measures, generated across the 4 visit times (stable and exacerbation day: 0,14 and 42) for the 66 exacerbation episodes, revealed three subgroups designated HG, HF, and GF reflecting predominance or equivalence of the two target bacterial groups. While the other subgroups showed no change at exacerbation, the HG cluster (n = 20) was characterized by G:F ratios that increased significantly at exacerbation and returned to baseline on recovery (p<0.00001); ratios in the HG group also correlated positively with inflammatory markers and negatively with FEV1. At exacerbation G:F showed a significant receiver-operator-characteristic curve to identify the HG subgroup (AUC 0.90, p<0.0001). CONCLUSIONS: The G:F ratio at exacerbation can be determined on a timescale compatible with decisions regarding clinical management. We propose that the G:F ratio has potential for use as a biomarker enabling selective use of antibiotics in COPD exacerbations and hence warrants further clinical evaluation.