Protected sampling is preferable in bronchoscopic studies of the airway microbiome

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.

Lung microbiome: new insights into the pathogenesis of respiratory diseases

The lungs were long thought to be sterile until technical advances uncovered the presence of the lung microbial community. The microbiome of healthy lungs is mainly derived from the upper respiratory tract (URT) microbiome but also has its own characteristic flora. The selection mechanisms in the lung, including clearance by coughing, pulmonary macrophages, the oscillation of respiratory cilia, and bacterial inhibition by alveolar surfactant, keep the microbiome transient and mobile, which is different from the microbiome in other organs. The pulmonary bacteriome has been intensively studied recently, but relatively little research has focused on the mycobiome and virome. This up-to-date review retrospectively summarizes the lung microbiome's history, composition, and function. We focus on the interaction of the lung microbiome with the oropharynx and gut microbiome and emphasize the role it plays in the innate and adaptive immune responses. More importantly, we focus on multiple respiratory diseases, including asthma, chronic obstructive pulmonary disease (COPD), fibrosis, bronchiectasis, and pneumonia. The impact of the lung microbiome on coronavirus disease 2019 (COVID-19) and lung cancer has also been comprehensively studied. Furthermore, by summarizing the therapeutic potential of the lung microbiome in lung diseases and examining the shortcomings of the field, we propose an outlook of the direction of lung microbiome research.

The Human Respiratory Microbiome: Current Understandings and Future Directions

Microorganisms colonize the human body. The lungs and respiratory tract, previously believed to be sterile, harbor diverse microbial communities and the genomes of bacteria (bacteriome), viruses (virome), and fungi (mycobiome). Recent advances in amplicon and shotgun metagenomic sequencing technologies and data-analyzing methods have greatly aided the identification and characterization of microbial populations from airways. The respiratory microbiome has been shown to play roles in human health and disease and is an area of rapidly emerging interest in pulmonary medicine. In this review, we provide updated information in the field by focusing on four lung conditions, including asthma, chronic obstructive pulmonary disease, cystic fibrosis, and idiopathic pulmonary fibrosis. We evaluate gut, oral, and upper airway microbiomes and how they contribute to lower airway flora. The discussion is followed by a systematic review of the lower airway microbiome in health and disease. We conclude with promising research avenues and implications for evolving therapeutics.

The lower airways microbiota and antimicrobial peptides indicate dysbiosis in sarcoidosis

BACKGROUND

The role of the pulmonary microbiome in sarcoidosis is unknown. The objectives of this study were the following: (1) examine whether the pulmonary fungal and bacterial microbiota differed in patients with sarcoidosis compared with controls; (2) examine whether there was an association between the microbiota and levels of the antimicrobial peptides (AMPs) in protected bronchoalveolar lavage (PBAL).

METHODS

Thirty-five sarcoidosis patients and 35 healthy controls underwent bronchoscopy and were sampled with oral wash (OW), protected BAL (PBAL), and left protected sterile brushes (LPSB). The fungal ITS1 region and the V3V4 region of the bacterial 16S rRNA gene were sequenced. Bioinformatic analyses were performed with QIIME 2. The AMPs secretory leucocyte protease inhibitor (SLPI) and human beta defensins 1 and 2 (hBD-1 and hBD-2), were measured in PBAL by enzyme-linked immunosorbent assay (ELISA).

RESULTS

Aspergillus dominated the PBAL samples in sarcoidosis. Differences in bacterial taxonomy were minor. There was no significant difference in fungal alpha diversity between sarcoidosis and controls, but the bacterial alpha diversity in sarcoidosis was significantly lower in OW (p = 0.047) and PBAL (p = 0.03) compared with controls. The beta diversity for sarcoidosis compared with controls differed for both fungi and bacteria. AMP levels were significantly lower in sarcoidosis compared to controls (SLPI and hBD-1: p < 0.01). No significant correlations were found between alpha diversity and AMPs.

CONCLUSIONS

The pulmonary fungal and bacterial microbiota in sarcoidosis differed from in controls. Lower antimicrobial peptides levels were seen in sarcoidosis, indicating an interaction between the microbiota and the innate immune system. Whether this dysbiosis represents a pathogenic mechanism in sarcoidosis needs to be confirmed in experimental studies. Video Abstract.

Peripheral blood transcriptomic clusters uncovered immune phenotypes of asthma

BACKGROUND

Transcriptomic analysis has been used to elucidate the complex pathogenesis of heterogeneous disease and may also contribute to identify potential therapeutic targets by delineating the hub genes. This study aimed to investigate whether blood transcriptomic clustering can distinguish clinical and immune phenotypes of asthmatics, and microbiome in asthmatics.

METHODS

Transcriptomic expression of peripheral blood mononuclear cells (PBMCs) from 47 asthmatics and 21 non-asthmatics was measured using RNA sequencing. A hierarchical clustering algorithm was used to classify asthmatics. Differentially expressed genes, clinical phenotypes, immune phenotypes, and microbiome of each transcriptomic cluster were assessed.

RESULTS

In asthmatics, three distinct transcriptomic clusters with numerously different transcriptomic expressions were identified. The proportion of severe asthmatics was highest in cluster 3 as 73.3%, followed by cluster 2 (45.5%) and cluster 1 (28.6%). While cluster 1 represented clinically non-severe T2 asthma, cluster 3 tended to include severe non-T2 asthma. Cluster 2 had features of both T2 and non-T2 asthmatics characterized by the highest serum IgE level and neutrophil-dominant sputum cell population. Compared to non-asthmatics, cluster 1 showed higher CCL23 and IL1RL1 expression while the expression of TREML4 was suppressed in cluster 3. CTSD and ALDH2 showed a significant positive linear relationship across three clusters in the order of cluster 1 to 3. No significant differences in the diversities of lung and gut microbiomes were observed among transcriptomic clusters of asthmatics and non-asthmatics. However, our study has limitations in that small sample size data were analyzed with unmeasured confounding factors and causal relationships or function pathways were not verified.

CONCLUSIONS

Genetic clustering based on the blood transcriptome may provide novel immunological insight, which can be biomarkers of asthma immune phenotypes. Trial registration Retrospectively registered.

Oral Microbes in Hospital-Acquired Pneumonia: Practice and Research Implications

BACKGROUND

Hospital-acquired pneumonia accounts for 25% of all health care-associated infections and is classified as either ventilator-associated or non-ventilator-associated pneumonia. Hospital-acquired pneumonia most frequently results from aspiration of oropharyngeal secretions into the lungs. Although preventive measures for ventilator-associated pneumonia are well established, few preventive measures exist for the nonventilator type.

OBJECTIVE

To (1) explore oral microbes associated with ventilator-associated and non-ventilator-associated pneumonia in acutely ill, adult hospitalized patients, and (2) provide evidence-based recommendations for measures to prevent pneumonia in hospitalized patients.

METHODS

A literature search was conducted using CINAHL, Academic Search Premier, Medline, and the Cochrane Library.

RESULTS

Ten studies were found that identified common oral microbes in ventilator-associated and non-ventilator-associated pneumonia, including Acinetobacter baumannii, Escherichia coli, Klebsiella pneumoniae, Pseudomonas aeruginosa, methicillin-resistant Staphylococcus aureus, S aureus, and Streptococcus pneumoniae. Collectively, oral colonization with E coli, P aeruginosa, methicillin-resistant S aureus, and S aureus increased the risk of nonventilator pneumonia. Findings also suggested microaspiration of colonized oral microbes into the lungs. Non-ventilator-associated pneumonia had similar colonization rates of gram-positive and gram-negative bacteria, whereas ventilator-associated pneumonia had greater colonization with gram-negative bacteria. The literature did not indicate a standard of oral care effective in all patient populations.

DISCUSSION

Oral care is an effective intervention to prevent hospital-acquired pneumonia by reducing pathogenic oral microbial colonization. The impact of different methods and timing of oral care on oral microbes should be further explored, particularly in patients not receiving mechanical ventilation.

CONCLUSIONS

Findings reaffirm the importance of consistent oral care in hospitalized patients. In addition, practices should be different in patients receiving mechanical ventilation versus patients not receiving ventilation. Results may also provide knowledge to inform future preventive measures for pneumonia, particularly for nonventilator pneumonia.

A longitudinal study of the pulmonary mycobiome in subjects with and without chronic obstructive pulmonary disease

Background

Few studies have examined the stability of the pulmonary mycobiome. We report longitudinal changes in the oral and pulmonary mycobiome of participants with and without COPD in a large-scale bronchoscopy study (MicroCOPD).

Methods

Repeated sampling was performed in 30 participants with and 21 without COPD. We collected an oral wash (OW) and a bronchoalveolar lavage (BAL) sample from each participant at two time points. The internal transcribed spacer 1 region of the ribosomal RNA gene cluster was PCR amplified and sequenced on an Illumina HiSeq sequencer. Differences in taxonomy, alpha diversity, and beta diversity between the two time points were compared, and we examined the effect of intercurrent antibiotic use.

Results

Sample pairs were dominated by Candida. We observed less stability in the pulmonary taxonomy compared to the oral taxonomy, additionally emphasised by a higher Yue-Clayton measure in BAL compared to OW (0.69 vs 0.22). No apparent effect was visually seen on taxonomy from intercurrent antibiotic use or participant category. We found no systematic variation in alpha diversity by time either in BAL (p-value 0.16) or in OW (p-value 0.97), and no obvious clusters on bronchoscopy number in PCoA plots. Pairwise distance analyses showed that OW samples from repeated sampling appeared more stable compared to BAL samples using the Bray-Curtis distance metric (p-value 0.0012), but not for Jaccard.

Conclusion

Results from the current study propose that the pulmonary mycobiome is less stable than the oral mycobiome, and neither COPD diagnosis nor intercurrent antibiotic use seemed to influence the stability.

The lower airways microbiome and antimicrobial peptides in idiopathic pulmonary fibrosis differ from chronic obstructive pulmonary disease

BACKGROUND

The lower airways microbiome and host immune response in chronic pulmonary diseases are incompletely understood. We aimed to investigate possible microbiome characteristics and key antimicrobial peptides and proteins in idiopathic pulmonary fibrosis (IPF) and chronic obstructive pulmonary disease (COPD).

METHODS

12 IPF patients, 12 COPD patients and 12 healthy controls were sampled with oral wash (OW), protected bronchoalveolar lavage (PBAL) and right lung protected sterile brushings (rPSB). The antimicrobial peptides and proteins (AMPs), secretory leucocyte protease inhibitor (SLPI) and human beta defensins 1 and 2 (hBD-1 & hBD-2), were measured in PBAL by enzyme linked immunosorbent assay (ELISA). The V3V4 region of the bacterial 16S rDNA gene was sequenced. Bioinformatic analyses were performed with QIIME 2.

RESULTS

hBD-1 levels in PBAL for IPF were lower compared with COPD. The predominant phyla in IPF were Firmicutes, Bacteroides and Actinobacteria; Proteobacteria were among top three in COPD. Differential abundance analysis at genus level showed significant differences between study groups for less abundant, mostly oropharyngeal, microbes. Alpha diversity was lower in IPF in PBAL compared to COPD (p = 0.03) and controls (p = 0.01), as well as in rPSB compared to COPD (p = 0.02) and controls (p = 0.04). Phylogenetic beta diversity showed significantly more similarity for IPF compared with COPD and controls. There were no significant correlations between alpha diversity and AMPs.

CONCLUSIONS

IPF differed in microbial diversity from COPD and controls, accompanied by differences in antimicrobial peptides. Beta diversity similarity between OW and PBAL in IPF may indicate that microaspiration contributes to changes in its microbiome.

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.

Semiquantitative Real-Time PCR to Distinguish Pneumocystis Pneumonia from Colonization in a Heterogeneous Population of HIV-Negative Immunocompromised Patients

Pneumocystis jirovecii is a threat to iatrogenically immunosuppressed individuals, a heterogeneous population at rapid growth. We assessed the ability of an in-house semiquantitative real-time PCR assay to discriminate Pneumocystis pneumonia (PCP) from colonization and identified risk factors for infection in these patients. Retrospectively, 242 PCR-positive patients were compared according to PCP status, including strata by immunosuppressive conditions, human immunodeficiency virus (HIV) infection excluded. Associations between host characteristics and cycle threshold (CT) values, semiquantitative real-time PCR correlates of fungal loads in lower respiratory tract specimens, were investigated. CT values differed significantly according to PCP status. Overall, a CT value of 36 allowed differentiation between PCP and colonization with sensitivity and specificity of 71.3% and 77.1%, respectively. A CT value of less than 31 confirmed PCP, whereas no CT value permitted exclusion. A considerable diversity was uncovered; solid organ transplant (SOT) recipients had significantly higher fungal loads than patients with hematological malignancies. In SOT recipients, a CT cutoff value of 36 resulted in sensitivity and specificity of 95.0% and 83.3%, respectively. In patients with hematological malignancies, a higher CT cutoff value of 37 improved sensitivity to 88.5% but reduced specificity to 66.7%. For other conditions, assay validity appeared inferior. Corticosteroid usage was an independent predictor of PCP in a multivariable analysis and was associated with higher fungal loads at PCP expression. Semiquantitative real-time PCR improves differentiation between PCP and colonization in immunocompromised HIV-negative individuals with acute respiratory syndromes. However, heterogeneity in disease evolution requires separate cutoff values across intrinsic and iatrogenic predisposition for predicting non-HIV PCP. IMPORTANCE Pneumocystis jirovecii is potentially life threatening to an increasing number of individuals with compromised immune systems. This microorganism can cause severe pneumonia in susceptible hosts, including patients with cancer and autoimmune diseases and people undergoing solid organ transplantation. Together, these patients constitute an ever-diverse population. In this paper, we demonstrate that the heterogeneity herein has important implications for how we diagnose and assess the risk of Pneumocystis pneumonia (PCP). Specifically, low loads of microorganisms are sufficient to cause infection in patients with blood cancer compared to those in solid organ recipients. With this new insight into host versus P. jirovecii biology, clinicians can manage patients at risk of PCP more accurately. As a result, we take a significant step toward offering precision medicine to a vulnerable patient population. One the one hand, these patients have propensity for adverse effects from antimicrobial treatment. On the other hand, this population is susceptible to life-threatening infections, including PCP.

The Effects of Corticosteroids on the Respiratory Microbiome: A Systematic Review

Background: Since its discovery, the respiratory microbiome has been implicated in the pathogenesis of multiple pulmonary diseases. Even though corticosteroid treatments are widely prescribed for pulmonary diseases, their effects on the respiratory microbiome are still poorly understood. This systematic review summarizes the current understanding of the effects of corticosteroids on the microbiome of the airways. Research Question: How does treatment with corticosteroids impact the respiratory microbiome? Study Design and Methods: According to the PRISMA guidelines, Embase, Medline, and the Cochrane Central Register of Controlled Trials (CENTRAL) databases were systematically searched for all observational or randomized-controlled studies comparing the microbiome parameters of patients receiving corticosteroids to those of controls. The primary outcomes of interest were changes in the diversity, composition and total burden of the respiratory microbiome as assessed by culture-independent molecular methods. Results: Out of 1,943 identified reports, five studies could be included: two on patients with asthma, two on patients with chronic obstructive pulmonary disease and one on patients with chronic rhinosinusitis. The studies were highly heterogeneous with regards to the methods used and the populations investigated. Microbiome diversity increased with corticosteroids at least transiently in three studies and decreased in one study. The effects of corticosteroids on the composition of the respiratory microbiome were significant but without a clear shared direction. A significant increase in microbial burden after corticosteroids was seen in one study. Interpretation: Data on the effect of corticosteroids on the respiratory microbiome are still limited, with considerable heterogeneity between studies. However, available data suggest that corticosteroid treatment may have significant effects on the composition and possibly the diversity of the respiratory microbiome. Further research is needed to better understand the influence of corticosteroids on the respiratory microbiome and thus better target its widespread therapeutic use.

Advances in asthma genetics

While asthma has a strong genetic component, our current ability to systematically understand and predict asthma risk remains low, despite over a hundred genetic associations. The reasons for this unfilled gap range from technical limitations of current approaches to fundamental deficiencies in the way we understand asthma. These are discussed in the context of genomic advances.

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-020-07252-z.

The airway fungal microbiome in asthma

BACKGROUND

Fungal involvement in asthma is associated with severe disease. The full spectrum of fungal species in asthma is not well described and is derived largely from insensitive culture techniques.

OBJECTIVES

To use high-throughput sequencing to describe the airway mycobiota in asthmatics with and without fungal sensitization and healthy controls; to compare samples representing different airway compartments; to determine whether the mycobiota was influenced by the fungal composition of outdoor air; and to compare findings with clinically relevant outcomes.

METHODS

We amplified the internal transcribed spacer region 2 of the nuclear ribosomal operon to identify the fungal species present. Ninety-seven subjects were recruited and provided sputum (83 asthmatics; 14 healthy subjects), with 29 also undergoing a bronchoscopy. A subset of airway samples were compared with matched outdoor air and mouthwash samples.

RESULTS

Two hundred and six taxa at the species level were identified in sputum, most at low relative abundance. Aspergillus fumigatus, Candida albicans and Mycosphaerella tassiana had the highest relative abundances and were the most prevalent species across all subjects. The airway mycobiota consisted of a complex community with high diversity between individuals. Notable shifts in the balance of fungi detected in the lung were associated with asthma status, asthma duration and biomarkers of inflammation. Aspergillus tubingensis, a member of the Aspergillus niger species complex, was most prevalent from bronchoscopic protected brush samples and significantly associated with a low sputum neutrophilia. Cryptococcus pseudolongus, from the Cryptococcus humicola species complex, was more abundant from bronchoscopy samples than sputum, and differentially more abundant in asthma than health.

CONCLUSIONS AND CLINICAL RELEVANCE

The airway mycobiota was dominated by a relatively small number of species, but was distinct from the oropharyngeal mycobiota and air samples. Members of the A. niger and C. humicola species complexes may play unexpected roles in the pathogenesis of asthma.

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 β 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 β 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.

Contrary to previous reports, in this study there were no significant associations between the lung microbiota in stable COPD and COPD exacerbation frequencyhttps://bit.ly/2ZVcNdG

Optimizing 16S rRNA gene profile analysis from low biomass nasopharyngeal and induced sputum specimens

BACKGROUND

Careful consideration of experimental artefacts is required in order to successfully apply high-throughput 16S ribosomal ribonucleic acid (rRNA) gene sequencing technology. Here we introduce experimental design, quality control and "denoising" approaches for sequencing low biomass specimens.

RESULTS

We found that bacterial biomass is a key driver of 16S rRNA gene sequencing profiles generated from bacterial mock communities and that the use of different deoxyribonucleic acid (DNA) extraction methods [DSP Virus/Pathogen Mini Kit® (Kit-QS) and ZymoBIOMICS DNA Miniprep Kit (Kit-ZB)] and storage buffers [PrimeStore® Molecular Transport medium (Primestore) and Skim-milk, Tryptone, Glucose and Glycerol (STGG)] further influence these profiles. Kit-QS better represented hard-to-lyse bacteria from bacterial mock communities compared to Kit-ZB. Primestore storage buffer yielded lower levels of background operational taxonomic units (OTUs) from low biomass bacterial mock community controls compared to STGG. In addition to bacterial mock community controls, we used technical repeats (nasopharyngeal and induced sputum processed in duplicate, triplicate or quadruplicate) to further evaluate the effect of specimen biomass and participant age at specimen collection on resultant sequencing profiles. We observed a positive correlation (r = 0.16) between specimen biomass and participant age at specimen collection: low biomass technical repeats (represented by < 500 16S rRNA gene copies/μl) were primarily collected at < 14 days of age. We found that low biomass technical repeats also produced higher alpha diversities (r = - 0.28); 16S rRNA gene profiles similar to no template controls (Primestore); and reduced sequencing reproducibility. Finally, we show that the use of statistical tools for in silico contaminant identification, as implemented through the decontam package in R, provides better representations of indigenous bacteria following decontamination.

CONCLUSIONS

We provide insight into experimental design, quality control steps and "denoising" approaches for 16S rRNA gene high-throughput sequencing of low biomass specimens. We highlight the need for careful assessment of DNA extraction methods and storage buffers; sequence quality and reproducibility; and in silico identification of contaminant profiles in order to avoid spurious results.

Sputum microbiota and inflammation at stable state and during exacerbations in a cohort of chronic obstructive pulmonary disease (COPD) patients

BACKGROUND

Exacerbations of chronic obstructive pulmonary disease (COPD) are debilitating events and spur disease progression. Infectious causes are frequent; however, it is unknown to what extent exacerbations are caused by larger shifts in the airways' microbiota. The aim of the current study was to analyse the changes in microbial composition between stable state and during exacerbations, and the corresponding immune response.

METHODS

The study sample included 36 COPD patients examined at stable state and exacerbation from the Bergen COPD Cohort and Exacerbations studies, and one patient who delivered sputum on 13 different occasions during the three-year study period. A physician examined the patients at all time points, and sputum induction was performed by stringent protocol. Only induced sputum samples were used in the current study, not spontaneously expectorated sputum. Sputum inflammatory markers (IL-6, IL-8, IL-18, IP-10, MIG, TNF-α) and antimicrobial peptides (AMPs, i.e. LL-37/hCAP-18, SLPI) were measured in supernatants, whereas target gene sequencing (16S rRNA) was performed on corresponding cell pellets. The microbiome bioinformatics platform QIIME2TM and the statistics environment R were applied for bioinformatics analyses.

RESULTS

Levels of IP-10, MIG, TNF-α and AMPs were significantly different between the two disease states. Of 36 sample pairs, 24 had significant differences in the 12 most abundant genera between disease states. The diversity was significantly different in several individuals, but not when data was analysed on a group level. The one patient case study showed longitudinal dynamics in microbiota unrelated to disease state.

CONCLUSION

Changes in the sputum microbiota with changing COPD disease states are common, and are accompanied by changes in inflammatory markers. However, the changes are highly individual and heterogeneous events.

The influence of the microbiome on respiratory health

The revolution in microbiota research over the past decade has provided invaluable knowledge about the function of the microbial species that inhabit the human body. It has become widely accepted that these microorganisms, collectively called 'the microbiota', engage in networks of interactions with each other and with the host that aim to benefit both the microbial members and the mammalian members of this unique ecosystem. The lungs, previously thought to be sterile, are now known to harbor a unique microbiota and, additionally, to be influenced by microbial signals from distal body sites, such as the intestine. Here we review the role of the lung and gut microbiotas in respiratory health and disease and highlight the main pathways of communication that underlie the gut-lung axis.

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.

Molecular Signatures of Non-typeable Haemophilus influenzae Lung Adaptation in Pediatric Chronic Lung Disease

Non-typeable Haemophilus influenzae (NTHi), an opportunistic pathogen of the upper airways of healthy children, can infect the lower airways, driving chronic lung disease. However, the molecular basis underpinning NTHi transition from a commensal to a pathogen is not clearly understood. Here, we performed comparative genomic and transcriptomic analyses of 12 paired, isogenic NTHi strains, isolated from the nasopharynx (NP) and bronchoalveolar lavage (BAL) of 11 children with chronic lung disease, to identify convergent molecular signatures associated with lung adaptation. Comparative genomic analyses of the 12 NP-BAL pairs demonstrated that five were genetically identical, with the remaining seven differing by only 1 to 3 mutations. Within-patient transcriptomic analyses identified between 2 and 58 differentially expressed genes in 8 of the 12 NP-BAL pairs, including pairs with no observable genomic changes. Whilst no convergence was observed at the gene level, functional enrichment analysis revealed significant under-representation of differentially expressed genes belonging to Coenzyme metabolism, Function unknown, Translation, ribosomal structure, and biogenesis Cluster of Orthologous Groups categories. In contrast, Carbohydrate transport and metabolism, Cell motility and secretion, Intracellular trafficking and secretion, and Energy production categories were over-represented. This observed trend amongst genetically unrelated NTHi strains provides evidence of convergent transcriptional adaptation of NTHi to pediatric airways that deserves further exploration. Understanding the pathoadaptative mechanisms that NTHi employs to infect and persist in the lower pediatric airways is essential for devising targeted diagnostics and treatments aimed at minimizing disease severity, and ultimately, preventing NTHi lung infections and subsequent chronic lung disease in children.

Microbial and host immune factors as drivers of COPD

Compartmentalisation of the respiratory tract microbiota in patients with different chronic obstructive pulmonary disease (COPD) severity degrees needs to be systematically investigated. In addition, it is unknown if the inflammatory and emphysematous milieux in patients with COPD are associated with changes in the respiratory tract microbiota and host macrophage gene expression.

We performed a cross-sectional study to compare non-COPD controls (n=10) to COPD patients (n=32) with different disease severity degrees. Samples (n=187) were obtained from different sites of the upper and lower respiratory tract. Microbiota analyses were performed by 16S ribosomal RNA gene sequencing and host gene expression analyses by quantitative real-time PCR of distinct markers of bronchoalveolar lavage cells.

Overall, the microbial communities of severe COPD (Global Initiative for Chronic Obstructive Lung Disease (GOLD) grade 3/4) patients clustered significantly differently to controls and less severe COPD (GOLD 1/2) patients (permutational multivariate ANOVA (MANOVA), p=0.001). However, we could not detect significant associations between the different sampling sites in the lower airways. In addition, the chosen set of host gene expression markers significantly separated COPD GOLD 3/4 patients, and we found correlations between the composition of the microbiota and the host data.

In conclusion, this study demonstrates associations between host gene expression and microbiota profiles that may influence the course of COPD.

Associations of the host immune response and a disordered microbiota in patients with different COPD severity degreeshttp://ow.ly/h2mW30k9Nua

The Lung Microbiome in Idiopathic Pulmonary Fibrosis: A Promising Approach for Targeted Therapies

This review focuses on the role of the lung microbiome in idiopathic pulmonary fibrosis. Although historically considered sterile, bacterial communities have now been well documented in lungs both in healthy and pathological conditions. Studies in idiopathic pulmonary fibrosis (IPF) suggest that increased bacterial burden and/or abundance of potentially pathogenic bacteria may drive disease progression, acute exacerbations, and mortality. More recent work has highlighted the interaction between the lung microbiome and the innate immune system in IPF, strengthening the argument for the role of both host and environment interaction in disease pathogenesis. Existing published data suggesting that the lung microbiome may represent a therapeutic target, via antibiotic administration, immunization against pathogenic organisms, or treatment directed at gastroesophageal reflux. Taken altogether, published literature suggests that the lung microbiome might serve in the future as a prognostic biomarker, a therapeutic target, and/or provide an explanation for disease pathogenesis in IPF.