BackgroundThe study of microbial communities has been revolutionised in recent years by the widespread adoption of culture independent analytical techniques such as 16S rRNA gene sequencing and metagenomics. One potential confounder of these sequence-based approaches is the presence of contamination in DNA extraction kits and other laboratory reagents.ResultsIn this study we demonstrate that contaminating DNA is ubiquitous in commonly used DNA extraction kits and other laboratory reagents, varies greatly in composition between different kits and kit batches, and that this contamination critically impacts results obtained from samples containing a low microbial biomass. Contamination impacts both PCR-based 16S rRNA gene surveys and shotgun metagenomics. We provide an extensive list of potential contaminating genera, and guidelines on how to mitigate the effects of contamination.ConclusionsThese results suggest that caution should be advised when applying sequence-based techniques to the study of microbiota present in low biomass environments. Concurrent sequencing of negative control samples is strongly advised.Electronic supplementary materialThe online version of this article (doi:10.1186/s12915-014-0087-z) contains supplementary material, which is available to authorized users.

Background Lateral flow device (LFD) viral antigen immunoassays have been developed around the world as diagnostic tests for SARS-CoV-2 infection. They have been proposed to deliver an infrastructure-light, cost-economical solution giving results within half an hour. Methods LFDs were initially reviewed by a Department of Health and Social Care team, part of the UK government, from which 64 were selected for further evaluation from 1st August to 15th December 2020. Standardised laboratory evaluations, and for those that met the published criteria, field testing in the Falcon-C19 research study and UK pilots were performed (UK COVID-19 testing centres, hospital, schools, armed forces). Findings 4/64 LFDs so far have desirable performance characteristics (orient Gene, Deepblue, Abbott and Innova SARS-CoV-2 Antigen Rapid Qualitative Test). All these LFDs have a viral antigen detection of >90% at 100,000 RNA copies/ml. 8951 Innova LFD tests were performed with a kit failure rate of 5.6% (502/8951, 95% CI: 5.1–6.1), false positive rate of 0.32% (22/6954, 95% CI: 0.20–0.48). Viral antigen detection/sensitivity across the sampling cohort when performed by laboratory scientists was 78.8% (156/198, 95% CI 72.4–84.3). Interpretation Our results suggest LFDs have promising performance characteristics for mass population testing and can be used to identify infectious positive individuals. The Innova LFD shows good viral antigen detection/sensitivity with excellent specificity, although kit failure rates and the impact of training are potential issues. These results support the expanded evaluation of LFDs, and assessment of greater access to testing on COVID-19 transmission. Funding Department of Health and Social Care. University of Oxford. Public Health England Porton Down, Manchester University NHS Foundation Trust, National Institute of Health Research.

BackgroundBronchiectasis is accompanied by chronic bronchial infection that may drive disease progression. However, the evidence base for antibiotic therapy is limited. DNA based methods offer better identification and quantification of microbial constituents of sputum than standard clinical culture and may help inform patient management strategies. Our study objective was to determine the longitudinal variability of the non-cystic fibrosis (CF) bronchiectasis microbiome in sputum with respect to clinical variables. Eighty-five patients with non-CF bronchiectasis and daily sputum production were recruited from outpatient clinics and followed for six months. Monthly sputum samples and clinical measurements were taken, together with additional samples during exacerbations. 16S rRNA gene sequencing of the sputum microbiota was successful for 381 samples from 76 patients and analysed in conjunction with clinical data.ResultsMicrobial communities were highly individual in composition and stability, usually with limited diversity and often containing multiple pathogens. When compared to DNA sequencing, microbial culture had restricted sensitivity in identifying common pathogens such as Pseudomonas aeruginosa, Haemophilus influenzae, Moraxella catarrhalis. With some exceptions, community characteristics showed poor correlations with clinical features including underlying disease, antibiotic use and exacerbations, with the subject showing the strongest association with community structure. When present, the pathogens mucoid Pseudomonas aeruginosa and Haemophilus influenzae may also shape the structure of the rest of the microbial community.ConclusionsThe use of microbial community analysis of sputum added to information from microbial culture. A simple model of exacerbations driven by bacterial overgrowth was not supported, suggesting a need for revision of principles for antibiotic therapy. In individual patients, the management of chronic bronchial infection may be improved by therapy specific to their microbiome, taking into account pathogen load, community stability, and acute and chronic community responses to antibiotics.

Bacterial infection commonly complicates inflammatory airway diseases such as chronic obstructive pulmonary disease (COPD). The mechanisms of increased infection susceptibility and how use of the commonly prescribed therapy inhaled corticosteroids (ICS) accentuates pneumonia risk in COPD are poorly understood. Here, using analysis of samples from patients with COPD, we show that ICS use is associated with lung microbiota disruption leading to proliferation of streptococcal genera, an effect that could be recapitulated in ICS-treated mice. To study mechanisms underlying this effect, we used cellular and mouse models of streptococcal expansion withStreptococcus pneumoniae, an important pathogen in COPD, to demonstrate that ICS impairs pulmonary clearance of bacteria through suppression of the antimicrobial peptide cathelicidin. ICS impairment of pulmonary immunity was dependent on suppression of cathelicidin because ICS had no effect on bacterial loads in mice lacking cathelicidin (Camp−/−) and exogenous cathelicidin prevented ICS-mediated expansion of streptococci within the microbiota and improved bacterial clearance. Suppression of pulmonary immunity by ICS was mediated by augmentation of the protease cathepsin D. Collectively, these data suggest a central role for cathepsin D/cathelicidin in the suppression of antibacterial host defense by ICS in COPD. Therapeutic restoration of cathelicidin to boost antibacterial immunity and beneficially modulate the lung microbiota might be an effective strategy in COPD.

Background Normal airway microbial communities play a central role in respiratory health but are poorly characterized. Cigarette smoking is the dominant global environmental influence on lung function, and asthma has become the most prevalent chronic respiratory disease worldwide. Both conditions have major microbial components that are incompletely defined. Methods We investigated airway bacterial communities in a general population sample of 529 Australian adults. Posterior oropharyngeal swabs were analyzed by sequencing of the 16S rRNA gene. The microbiota were characterized according to their prevalence, abundance and network memberships. Findings The microbiota were similar across the general population, and were strongly organized into co-abundance networks. Smoking was associated with diversity loss, negative effects on abundant taxa, profound alterations to network structure and expansion of Streptococcus spp. By contrast, the asthmatic microbiota were selectively affected by an increase in Neisseria spp. and by reduced numbers of low abundance but prevalent organisms. Interpretation Our study shows that the healthy airway microbiota in this population were contained within a highly structured ecosystem, suggesting balanced relationships between the microbiome and human host factors. The marked abnormalities in smokers may contribute to chronic obstructive pulmonary disease (COPD) and lung cancer. The narrow spectrum of abnormalities in asthmatics encourages investigation of damaging and protective effects of specific bacteria. Funding The study was funded by the Asmarley Trust and a Wellcome Joint Senior Investigator Award to WOCC and MFM (WT096964MA and WT097117MA). The Busselton Healthy Ageing Study is supported by the Government of Western Australia (Office of Science, Department of Health) the City of Busselton, and private donations.

The study of microbial communities has been revolutionised in recent years by the widespread adoption of culture independent analytical techniques such as 16S rRNA gene sequencing and metagenomics. One potential confounder of these sequence-based approaches is the presence of contamination in DNA extraction kits and other laboratory reagents. In this study we demonstrate that contaminating DNA is ubiquitous in commonly used DNA extraction kits, varies greatly in composition between different kits and kit batches, and that this contamination critically impacts results obtained from samples containing a low microbial biomass. Contamination impacts both PCR based 16S rRNA gene surveys and shotgun metagenomics. These results suggest that caution should be advised when applying sequence-based techniques to the study of microbiota present in low biomass environments. We provide an extensive list of potential contaminating genera, and guidelines on how to mitigate the effects of contamination. Concurrent sequencing of negative control samples is strongly advised.

Lung diseases due to infection and dysbiosis affect hundreds of millions of people world-wide. Microbial communities at the airway mucosal barrier are conserved and highly ordered, reflecting symbiosis and co-evolution with human host factors. Freed of selection to digest nutrients for the host, the airway microbiome underpins cognate management of mucosal immunity and pathogen resistance. We show here the results of the first systematic culture and whole-genome sequencing of the principal airway bacterial species, identifying abundant novel organisms within the genera Streptococcus, Pauljensenia, Neisseria and Gemella. Bacterial genomes were enriched for genes encoding antimicrobial synthesis, adhesion and biofilm formation, immune modulation, iron utilisation, nitrous oxide (NO) metabolism and sphingolipid signalling. RNA-targeting CRISPR elements in some taxa suggest the potential to prevent or treat specific viral infections. Homologues of human RO60 present in Neisseria spp. provide a possible respiratory primer for autoimmunity in systemic lupus erythematosus (SLE) and Sjogren syndrome. We interpret the structure and biogeography of airway microbial communities from clinical surveys in the context of whole-genome content, identifying features of airway dysbiosis that may presage breakdown of homeostasis during acute attacks of asthma and chronic obstructive pulmonary disease (COPD). We match the gene content of isolates to human transcripts and metabolites expressed late in airway epithelial differentiation, identifying pathways that can sustain host interactions with the microbiota. Our results provide a systematic basis for decrypting interactions between commensals, pathogens, and mucosal immunity in lung diseases of global significance.

Background: Cystic fibrosis (CF) and non-CF bronchiectasis (BX) are lung diseases characterised by severe chronic infections. Fungal and bacterial components of infection are both recognized. Recent molecular investigation of sputum from patients with CF and BX has revealed a complex mycobiome. However, little is known about how fungal and bacterial organisms interact or whether the interactions impact on disease outcomes. Methods: Quantitative PCR and next generation sequencing of ITS2 and 16S rRNA gene was carried out on 107 patients with CF and BX and defined clinical fungal infection status. Fungal and bacterial communities were explored using supervised and unsupervised machine learning to understand associations between fungal and bacterial communities and their relationship to disease. Results: Fungal and bacterial communities both had significantly higher biomass and lower diversity in CF compared to BX patients. Random forest modelling demonstrated that the fungal and bacterial communities were distinct between CF and BX patients. Within the CF group, bacterial communities contained no predictive signal for fungal disease status. Neither bacterial nor fungal community composition were predictive of the presence of CF pulmonary exacerbation (CFPE). Intra-kingdom correlations were far stronger than those between the two kingdoms. Dirichlet mixture components analysis identified two distinct clusters of bacteria related to the relative abundance of Pseudomonas. Fungal community composition contained no predictive signal for bacterial clusters. Conclusions: Clear changes in diversity were observed between patients with different clinical disease status. Although our results demonstrate that bacterial community composition differs in the presence of fungal disease, no direct relationship between bacterial and fungal OTUs was found.