Lower airway microbiota in COPD and healthy controls.

BACKGROUND: The lower airway microbiota in patients with chronic obstructive pulmonary disease (COPD) are likely altered compared with the microbiota in healthy individuals. Information on how the microbiota is affected by smoking, use of inhaled corticosteroids (ICS) and COPD severity is still scarce. METHODS: In the MicroCOPD Study, participant characteristics were obtained through standardised questionnaires and clinical measurements at a single centre from 2012 to 2015. Protected bronchoalveolar lavage samples from 97 patients with COPD and 97 controls were paired-end sequenced with the Illumina MiSeq System. Data were analysed in QIIME 2 and R. RESULTS: Alpha-diversity was lower in patients with COPD than controls (Pielou evenness: COPD=0.76, control=0.80, p=0.004; Shannon entropy: COPD=3.98, control=4.34, p=0.01). Beta-diversity differed with smoking only in the COPD cohort (weighted UniFrac: permutational analysis of variance R2=0.04, p=0.03). Nine genera were differentially abundant between COPD and controls. Genera enriched in COPD belonged to the Firmicutes phylum. Pack years were linked to differential abundance of taxa in controls only (ANCOM-BC (Analysis of Compositions of Microbiomes with Bias Correction) log-fold difference/q-values: Haemophilus -0.05/0.048; Lachnoanaerobaculum -0.04/0.03). Oribacterium was absent in smoking patients with COPD compared with non-smoking patients (ANCOM-BC log-fold difference/q-values: -1.46/0.03). We found no associations between the microbiota and COPD severity or ICS. CONCLUSION: The lower airway microbiota is equal in richness in patients with COPD to controls, but less even. Genera from the Firmicutes phylum thrive particularly in COPD airways. Smoking has different effects on diversity and taxonomic abundance in patients with COPD compared with controls. COPD severity and ICS use were not linked to the lower airway microbiota.

Periodontitis is associated with airflow obstruction in the Malmö Offspring Dental Study.

AIM: To investigate the association between periodontitis and lung function in the Malmö Offspring Dental Study. MATERIALS AND METHODS: In all 1001 individuals (49.9% female, mean age: 44.6) from Malmö Offspring Dental Study were included. Periodontitis was assessed by a full-mouth examination protocol including bleeding on probing and classified according to the American Academy of Periodontology/Center for Disease Control definitions. Forced expiratory volume in 1 s (FEV1 ) and forced vital capacity (FVC) were expressed as absolute values and %predicted according to Global Lung Function Initiative reference values. FEV1 , FVC and FEV1 /FVC were analysed in relation to periodontal status using linear regression. RESULTS: Severe periodontitis was found in 7% of the population. Adjusted regression models showed significant associations between lung function and severe periodontitis with 2.1 unit lower FEV1 /FVC ratio (95% CI: -3.91, -0.23) and odds ratio (adjusted) of 2.56 (95% CI: 1.40, 4.75, p = .003) for airflow obstruction (FEV1 /FVC less than the lower limit of normal) if having severe periodontitis. Lower values of %predicted FEV1 and %predicted FVC, but not FEV1 /FVC, were found in individuals with >25% bleeding on probing. CONCLUSIONS: Severe periodontitis was associated with lower FEV1 /FVC ratio and airflow obstruction in the present cohort. More large-scale prospective studies and intervention studies are required for a comprehensive evaluation.

Repeated bronchoscopy in health and obstructive lung disease: is the airway microbiome stable?

OBJECTIVE: Little is known concerning the stability of the lower airway microbiome. We have compared the microbiota identified by repeated bronchoscopy in healthy subjects and patients with ostructive lung diseaseases (OLD). METHODS: 21 healthy controls and 41 patients with OLD completed two bronchoscopies. In addition to negative controls (NCS) and oral wash (OW) samples, we gathered protected bronchoalveolar lavage in two fractions (PBAL1 and PBAL2) and protected specimen brushes (PSB). After DNA extraction, we amplified the V3V4 region of the 16S rRNA gene, and performed paired-end sequencing (Illumina MiSeq). Initial bioinformatic processing was carried out in the QIIME-2 pipeline, identifying amplicon sequence variants (ASVs) with the DADA2 algorithm. Potentially contaminating ASVs were identified and removed using the decontam package in R and the sequenced NCS. RESULTS: A final table of 551 ASVs consisted of 19 × 106 sequences. Alpha diversity was lower in the second exam for OW samples, and borderline lower for PBAL1, with larger differences in subjects not having received intercurrent antibiotics. Permutational tests of beta diversity indicated that within-individual changes were significantly lower than between-individual changes. A non-parametric trend test showed that differences in composition between the two exams (beta diversity) were largest in the PSBs, and that these differences followed a pattern of PSB > PBAL2 > PBAL1 > OW. Time between procedures was not associated with increased diversity. CONCLUSION: The airways microbiota varied between examinations. However, there is compositional microbiota stability within a person, beyond that of chance, supporting the notion of a transient airways microbiota with a possibly more stable individual core microbiome.

The pulmonary mycobiome-A study of subjects with and without chronic obstructive pulmonary disease.

BACKGROUND: The fungal part of the pulmonary microbiome (mycobiome) is understudied. We report the composition of the oral and pulmonary mycobiome in participants with COPD compared to controls in a large-scale single-centre bronchoscopy study (MicroCOPD). METHODS: Oral wash and bronchoalveolar lavage (BAL) was collected from 93 participants with COPD and 100 controls. Fungal DNA was extracted before sequencing of the internal transcribed spacer 1 (ITS1) region of the fungal ribosomal RNA gene cluster. Taxonomic barplots were generated, and we compared taxonomic composition, Shannon index, and beta diversity between study groups, and by use of inhaled steroids. RESULTS: The oral and pulmonary mycobiomes from controls and participants with COPD were dominated by Candida, and there were more Candida in oral samples compared to BAL for both study groups. Malassezia and Sarocladium were also frequently found in pulmonary samples. No consistent differences were found between study groups in terms of differential abundance/distribution. Alpha and beta diversity did not differ between study groups in pulmonary samples, but beta diversity varied with sample type. The mycobiomes did not seem to be affected by use of inhaled steroids. CONCLUSION: Oral and pulmonary samples differed in taxonomic composition and diversity, possibly indicating the existence of a pulmonary mycobiome.

Exploring protocol bias in airway microbiome studies: one versus two PCR steps and 16S rRNA gene region V3 V4 versus V4.

BACKGROUND: Studies on the airway microbiome have been performed using a wide range of laboratory protocols for high-throughput sequencing of the bacterial 16S ribosomal RNA (16S rRNA) gene. We sought to determine the impact of number of polymerase chain reaction (PCR) steps (1- or 2- steps) and choice of target marker gene region (V3 V4 and V4) on the presentation of the upper and lower airway microbiome. Our analyses included lllumina MiSeq sequencing following three setups: Setup 1 (2-step PCR; V3 V4 region), Setup 2 (2-step PCR; V4 region), Setup 3 (1-step PCR; V4 region). Samples included oral wash, protected specimen brushes and protected bronchoalveolar lavage (healthy and obstructive lung disease), and negative controls. RESULTS: The number of sequences and amplicon sequence variants (ASV) decreased in order setup1 > setup2 > setup3. This trend appeared to be associated with an increased taxonomic resolution when sequencing the V3 V4 region (setup 1) and an increased number of small ASVs in setups 1 and 2. The latter was considered a result of contamination in the two-step PCR protocols as well as sequencing across multiple runs (setup 1). Although genera Streptococcus, Prevotella, Veillonella and Rothia dominated, differences in relative abundance were observed across all setups. Analyses of beta-diversity revealed that while oral wash samples (high biomass) clustered together regardless of number of PCR steps, samples from the lungs (low biomass) separated. The removal of contaminants identified using the Decontam package in R, did not resolve differences in results between sequencing setups. CONCLUSIONS: Differences in number of PCR steps will have an impact of final bacterial community descriptions, and more so for samples of low bacterial load. Our findings could not be explained by differences in contamination levels alone, and more research is needed to understand how variations in PCR-setups and reagents may be contributing to the observed protocol bias.

The airway microbiota and exacerbations of COPD.

AIM: The aim of this study was to investigate whether the compositionality of the lower airway microbiota predicts later exacerbation risk in persons with COPD in a cohort study. MATERIALS AND METHODS: We collected lower airways microbiota samples by bronchoalveolar lavage and protected specimen brushes, and oral wash samples from 122 participants with COPD. Bacterial DNA was extracted from all samples, before we sequenced the V3-V4 region of the 16S RNA gene. The frequency of moderate and severe COPD exacerbations was surveyed in telephone interviews and in a follow-up visit. Compositional taxonomy and α and ß diversity were compared between participants with and without later exacerbations. RESULTS: The four most abundant phyla were Firmicutes, Bacteroidetes, Proteobacteria and Fusobacteria in both groups, and the four most abundant genera were Streptococcus, Veillonella, Prevotella and Gemella. The relative abundances of different taxa showed a large variation between samples and individuals, and no statistically significant difference of either compositional taxonomy, or α or ß diversity could be found between participants with and without COPD exacerbations within follow-up. CONCLUSION: The findings from the current study indicate that individual differences in the lower airway microbiota in persons with COPD far outweigh group differences between frequent and nonfrequent COPD exacerbators, and that the compositionality of the microbiota is so complex as to present large challenges for use as a biomarker of later exacerbations.

Laboratory contamination in airway microbiome studies.

BACKGROUND: The low bacterial load in samples acquired from the lungs, have made studies on the airway microbiome vulnerable to contamination from bacterial DNA introduced during sampling and laboratory processing. We have examined the impact of laboratory contamination on samples collected from the lower airways by protected (through a sterile catheter) bronchoscopy and explored various in silico approaches to dealing with the contamination post-sequencing. Our analyses included quantitative PCR and targeted amplicon sequencing of the bacterial 16S rRNA gene. RESULTS: The mean bacterial load varied by sample type for the 23 study subjects (oral wash>1st fraction of protected bronchoalveolar lavage>protected specimen brush>2nd fraction of protected bronchoalveolar lavage; p < 0.001). By comparison to a dilution series of know bacterial composition and load, an estimated 10-50% of the bacterial community profiles for lower airway samples could be traced back to contaminating bacterial DNA introduced from the laboratory. We determined the main source of laboratory contaminants to be the DNA extraction kit (FastDNA Spin Kit). The removal of contaminants identified using tools within the Decontam R package appeared to provide a balance between keeping and removing taxa found in both negative controls and study samples. CONCLUSIONS: The influence of laboratory contamination will vary across airway microbiome studies. By reporting estimates of contaminant levels and taking use of contaminant identification tools (e.g. the Decontam R package) based on statistical models that limit the subjectivity of the researcher, the accuracy of inter-study comparisons can be improved.

Protected sampling is preferable in bronchoscopic studies of the airway microbiome.

The aim was to evaluate susceptibility of oropharyngeal contamination with various bronchoscopic sampling techniques. 67 patients with obstructive lung disease and 58 control subjects underwent bronchoscopy with small-volume lavage (SVL) through the working channel, protected bronchoalveolar lavage (PBAL) and bilateral protected specimen brush (PSB) sampling. Subjects also provided an oral wash (OW) sample, and negative control samples were gathered for each bronchoscopy procedure. DNA encoding bacterial 16S ribosomal RNA was sequenced and bioinformatically processed to cluster into operational taxonomic units (OTU), assign taxonomy and obtain measures of diversity. The proportion of Proteobacteria increased, whereas Firmicutes diminished in the order OW, SVL, PBAL, PSB (p<0.01). The alpha-diversity decreased in the same order (p<0.01). Also, beta-diversity varied by sampling method (p<0.01), and visualisation of principal coordinates analyses indicated that differences in diversity were smaller between OW and SVL and OW and PBAL samples than for OW and the PSB samples. The order of sampling (left versus right first) did not influence alpha- or beta-diversity for PSB samples. Studies of the airway microbiota need to address the potential for oropharyngeal contamination, and protected sampling might represent an acceptable measure to minimise this problem.

Comparing microbiota profiles in induced and spontaneous sputum samples in COPD patients.

BACKGROUND: Induced and spontaneous sputum are used to evaluate the airways microbiota. Whether the sputum types can be used interchangeably in microbiota research is unknown. Our aim was to compare microbiota in induced and spontaneous sputum from COPD patients sampled during the same consultation. METHODS: COPD patients from Bergen, Norway, were followed between 2006/2010, examined during the stable state and exacerbations. 30 patients delivered 36 sample pairs. DNA was extracted by enzymatic and mechanical lysis methods. The V3-V4 region of the 16S rRNA gene was PCR-amplified and prepared for paired-end sequencing. Illumina Miseq System was used for sequencing, and Quantitative Insights Into Microbial Ecology (QIIME) and Stata were used for bioinformatics and statistical analyses. RESULTS: Approximately 4 million sequences were sorted into 1004 different OTUs and further assigned to 106 different taxa. Pair-wise comparison of both taxonomic composition and beta-diversity revealed significant differences in one or both parameters in 1/3 of sample pairs. Alpha-diversity did not differ. Comparing abundances for each taxa identified, showed statistically significant differences between the mean abundances in induced versus spontaneous samples for 15 taxa when disease state was considered. This included potential pathogens like Haemophilus and Moraxella. CONCLUSION: When studying microbiota in sputum samples one should take into consideration how samples are collected and avoid the usage of both induced and spontaneous sputum in the same study.