Cystic Fibrosis Lung Microbiota Research Articles

Antibiofilm activity of Prevotella species from the cystic fibrosis lung microbiota against Pseudomonas aeruginosa

It is increasingly recognized that interspecies interactions may modulate the pathogenicity of Pseudomonas aeruginosa during chronic lung infections. Nevertheless, while the interaction between P. aeruginosa and pathogenic microorganisms co-infecting the lungs has been widely investigated, little is known about the influence of other members of the lung microbiota on the infection process. In this study, we focused on investigating the impact of Prevotella species isolated from the sputum of people with cystic fibrosis (pwCF) on biofilm formation and virulence factor production by P. aeruginosa. Screening of a representative collection of Prevotella species recovered from clinical samples showed that several members of this genus (8 out 10 isolates) were able to significantly reduce biofilm formation of P. aeruginosa PAO1, without impact on growth. Among the tested isolates, the strongest biofilm-inhibitory activity was observed for Prevotella intermedia and Prevotella nigrescens, which caused a reduction of up to 90% in the total biofilm biomass of several P. aeruginosa isolates from pwCF. In addition, a strain-specific effect of P. nigrescens on the ability of P. aeruginosa to produce proteases and pyocyanin was observed, with significant alterations in the levels of these virulence factors detected in LasR mutant strains. Overall, these results suggest that non-pathogenic bacteria from the lung microbiota may regulate pathogenicity traits of P. aeruginosa, and possibly affect the outcome of chronic lung infections.

Respiratory Viruses and Cystic Fibrosis.

The threat of respiratory virus infection to human health and well-being has been clearly highlighted by the coronavirus disease 2019 (COVID-19) pandemic. For people with cystic fibrosis (CF), the clinical significance of viral infections long predated the emergence of severe acute respiratory syndrome coronavirus 2. This article reviews the epidemiology, diagnosis, and treatment of respiratory virus infection in the context of CF as well as the current understanding of interactions between viruses and other microorganisms in the CF lung. The incidence of respiratory virus infection in CF varies by age with young children typically experiencing more frequent episodes than adolescents and adults. At all ages, respiratory viruses are very common in CF and are associated with pulmonary exacerbations. Respiratory viruses are identified at up to 69% of exacerbations, while viruses are also frequently detected during clinical stability. The full impact of COVID-19 in CF is yet to be established. Early studies found that rates of COVID-19 were lower in CF cohorts than in the general population. The reasons for this are unclear but may be related to the effects of shielding, infection control practices, maintenance CF therapies, or the inflammatory milieu in the CF lung. Observational studies have consistently identified that prior solid organ transplantation is a key risk factor for poor outcomes from COVID-19 in CF. Several key priorities for future research are highlighted. First, the impact of highly effective CFTR modulator therapy on the epidemiology and pathophysiology of viral infections in CF requires investigation. Second, the impact of respiratory viruses on the development and dynamics of the CF lung microbiota is poorly understood and viral infection may have important interactions with bacteria and fungi in the airway. Finally, bacteriophages represent a key focus of future investigation both for their role in transmission of antimicrobial resistance and as a promising treatment modality for multiresistant pathogens.

Quick and wide-range taxonomical repertoire establishment of the cystic fibrosis lung microbiota by tandem mass spectrometry on sputum samples.

Microorganisms proteotyping by tandem mass spectrometry has been recently shown as a powerful methodology to identify the wide-range taxonomy and biomass of microbiota. Sputum is the recommended specimen for routine microbiological monitoring of Cystic Fibrosis (CF) patients but has been rarely submitted to tandem mass spectrometry-based proteotyping. In this study, we compared the microbial components of spontaneous and induced sputum samples from three cystic fibrosis patients. Although the presence of microbial proteins is much lower than host proteins, we report that the microbiota’s components present in the samples can be identified, as well as host biomarkers and functional insights into the microbiota. No significant difference was found in microorganism abundance between paired spontaneous and induced sputum samples. Microbial proteins linked to resistance, iron uptake, and biofilm-forming ability were observed in sputa independently of the sampling method. This unbiased and enlarged view of the CF microbiome could be highly complementary to culture and relevant for the clinical management of CF patients by improving knowledge about the host-pathogen dynamics and CF pathophysiology.

WS13.2 Metaproteomics profiling of the dynamic of the whole microbial components of the cystic fibrosis lung microbiota during CFTR modulator therapy

WS13.2 Metaproteomics profiling of the dynamic of the whole microbial components of the cystic fibrosis lung microbiota during CFTR modulator therapy

Bioorthogonal non-canonical amino acid tagging reveals translationally active subpopulations of the cystic fibrosis lung microbiota

Culture-independent studies of cystic fibrosis lung microbiota have provided few mechanistic insights into the polymicrobial basis of disease. Deciphering the specific contributions of individual taxa to CF pathogenesis requires comprehensive understanding of their ecophysiology at the site of infection. We hypothesize that only a subset of CF microbiota are translationally active and that these activities vary between subjects. Here, we apply bioorthogonal non-canonical amino acid tagging (BONCAT) to visualize and quantify bacterial translational activity in expectorated sputum. We report that the percentage of BONCAT-labeled (i.e. active) bacterial cells varies substantially between subjects (6-56%). We use fluorescence-activated cell sorting (FACS) and genomic sequencing to assign taxonomy to BONCAT-labeled cells. While many abundant taxa are indeed active, most bacterial species detected by conventional molecular profiling show a mixed population of both BONCAT-labeled and unlabeled cells, suggesting heterogeneous growth rates in sputum. Differentiating translationally active subpopulations adds to our evolving understanding of CF lung disease and may help guide antibiotic therapies targeting bacteria most likely to be susceptible.

Lung function and microbiota diversity in cystic fibrosis

BackgroundChronic infection and concomitant airway inflammation is the leading cause of morbidity and mortality for people living with cystic fibrosis (CF). Although chronic infection in CF is undeniably polymicrobial, involving a lung microbiota, infection surveillance and control approaches remain underpinned by classical aerobic culture-based microbiology. How to use microbiomics to direct clinical management of CF airway infections remains a crucial challenge. A pivotal step towards leveraging microbiome approaches in CF clinical care is to understand the ecology of the CF lung microbiome and identify ecological patterns of CF microbiota across a wide spectrum of lung disease. Assessing sputum samples from 299 patients attending 13 CF centres in Europe and the USA, we determined whether the emerging relationship of decreasing microbiota diversity with worsening lung function could be considered a generalised pattern of CF lung microbiota and explored its potential as an informative indicator of lung disease state in CF.ResultsWe tested and found decreasing microbiota diversity with a reduction in lung function to be a significant ecological pattern. Moreover, the loss of diversity was accompanied by an increase in microbiota dominance. Subsequently, we stratified patients into lung disease categories of increasing disease severity to further investigate relationships between microbiota characteristics and lung function, and the factors contributing to microbiota variance. Core taxa group composition became highly conserved within the severe disease category, while the rarer satellite taxa underpinned the high variability observed in the microbiota diversity. Further, the lung microbiota of individual patient were increasingly dominated by recognised CF pathogens as lung function decreased. Conversely, other bacteria, especially obligate anaerobes, increasingly dominated in those with better lung function. Ordination analyses revealed lung function and antibiotics to be main explanators of compositional variance in the microbiota and the core and satellite taxa. Biogeography was found to influence acquisition of the rarer satellite taxa.ConclusionsOur findings demonstrate that microbiota diversity and dominance, as well as the identity of the dominant bacterial species, in combination with measures of lung function, can be used as informative indicators of disease state in CF.BBFJdPr3cu-jH3LTAhe361Video

P131 Pseudomonas aeruginosa gene expression changes when co-cultured with common cystic fibrosis lung microbiota in an artificial sputum model

P131 Pseudomonas aeruginosa gene expression changes when co-cultured with common cystic fibrosis lung microbiota in an artificial sputum model

Investigating evolution of the paediatric cystic fibrosis lung microbiota using induced sputum sampling and culture-independent techniques

Background Children with cystic fibrosis are frequently non-productive of sputum even during exacerbation. Current routine sampling methods are either invasive (Bronchoalveolar lavage; BAL) or insensitive (cough swab) which makes pathogen surveillance challenging. We investigated induced sputum (IS) as a promising complementary sampling technique, looking at both its comparison to BAL and the evolution of the lung microbiota across children aged 0.5–18 years. Methods BAL and IS samples were collected as part of the CF-SpIT study (UKCRN14615; ISRCTNR12473810). DNA was extracted from samples and Illumina NextSeq sequencing of the 16S rRNA gene V4 region was performed. Bioinformatics data processing was carried out using Mothur. Microsoft Excel and R statistical software were used for downstream analyses. Results Comparison of the microbiota of 30 BAL-IS matched patient samples indicated that at a presence/absence level, IS captured >80 % of the pathogens observed in BAL samples. These findings validated the expansion of the study to 136 un-matched IS sputum samples, and we found that as patient age increased, bacterial diversity decreased, and changes in the abundance of key genera occurred over time. Both Neisseria and Haemophilus decreased with age, whilst Pseudomonas and a sub-group of Prevotella increased. Conclusions Here we uniquely demonstrate using culture-independent techniques that IS captures the majority of the bacterial diversity observed in BAL samples. The age associated decline in lung microbiota diversity, previously documented using BAL samples, can also be captured using IS samples. This suggests that surveillance of microbiota evolution may be possible using this method.

How can the cystic fibrosis respiratory microbiome influence our clinical decision-making?

Almost 15 years have now passed since bacterial community profiling techniques were first used to analyse respiratory samples from people with cystic fibrosis. Since then, many different analytical approaches have been used to try to better understand the contribution of the cystic fibrosis lung microbiota to disease, with varying degrees of success. We examine the extent to which cystic fibrosis respiratory microbiome research has been successful in informing clinical decision-making, and highlight areas that we believe have the potential to yield important insight. Recent research on the cystic fibrosis lung microbiome can be broadly divided into efforts to better characterize microbiota composition, particularly relative to key clinical events, and attempts to understand the cystic fibrosis lung microbiology as an interactive microbial system. The latter, in particular, has led to the development of a number of models in which microbiome-mediated processes precipitate clinical events. Growing technological sophistication is enabling increasingly detailed microbiological data to be generated from cystic fibrosis respiratory samples. However, translating these data into clinically useful measures that accurately predict outcomes and guide treatments remains a formidable challenge. The development of systems biology approaches that enable the integration of complex microbiome and host-derived data provide an exciting opportunity to address this goal.

Individual Patterns of Complexity in Cystic Fibrosis Lung Microbiota, Including Predator Bacteria, over a 1-Year Period.

ABSTRACTCystic fibrosis (CF) lung microbiota composition has recently been redefined by the application of next-generation sequencing (NGS) tools, identifying, among others, previously undescribed anaerobic and uncultivable bacteria. In the present study, we monitored the fluctuations of this ecosystem in 15 CF patients during a 1-year follow-up period, describing for the first time, as far as we know, the presence of predator bacteria in the CF lung microbiome. In addition, a new computational model was developed to ascertain the hypothetical ecological repercussions of a prey-predator interaction in CF lung microbial communities. Fifteen adult CF patients, stratified according to their pulmonary function into mild (n = 5), moderate (n = 9), and severe (n = 1) disease, were recruited at the CF unit of the Ramón y Cajal University Hospital (Madrid, Spain). Each patient contributed three or four induced sputum samples during a 1-year follow-up period. Lung microbiota composition was determined by both cultivation and NGS techniques and was compared with the patients’ clinical variables. Results revealed a particular microbiota composition for each patient that was maintained during the study period, although some fluctuations were detected without any clinical correlation. For the first time, Bdellovibrio and Vampirovibrio predator bacteria were shown in CF lung microbiota and reduced-genome bacterial parasites of the phylum Parcubacteria were also consistently detected. The newly designed computational model allows us to hypothesize that inoculation of predators into the pulmonary microbiome might contribute to the control of chronic colonization by CF pathogens in early colonization stages.

WS03.7 Coexistence of prey and predator bacteria in cystic fibrosis lung microbiota

WS03.7 Coexistence of prey and predator bacteria in cystic fibrosis lung microbiota

Strong incidence of Pseudomonas aeruginosa on bacterial rrs and ITS genetic structures of cystic fibrosis sputa.

Cystic fibrosis (CF) lungs harbor a complex community of interacting microbes, including pathogens like Pseudomonas aeruginosa. Meta-taxogenomic analysis based on V5-V6 rrs PCR products of 52 P. aeruginosa-positive (Pp) and 52 P. aeruginosa-negative (Pn) pooled DNA extracts from CF sputa suggested positive associations between P. aeruginosa and Stenotrophomonas and Prevotella, but negative ones with Haemophilus, Neisseria and Burkholderia. Internal Transcribed Spacer analyses (RISA) from individual DNA extracts identified three significant genetic structures within the CF cohorts, and indicated an impact of P. aeruginosa. RISA clusters Ip and IIIp contained CF sputa with a P. aeruginosa prevalence above 93%, and of 24.2% in cluster IIp. Clusters Ip and IIIp showed lower RISA genetic diversity and richness than IIp. Highly similar cluster IIp RISA profiles were obtained from two patients harboring isolates of a same P. aeruginosa clone, suggesting convergent evolution in the structure of their microbiota. CF patients of cluster IIp had received significantly less antibiotics than patients of clusters Ip and IIIp but harbored the most resistant P. aeruginosa strains. Patients of cluster IIIp were older than those of Ip. The effects of P. aeruginosa on the RISA structures could not be fully dissociated from the above two confounding factors but several trends in these datasets support the conclusion of a strong incidence of P. aeruginosa on the genetic structure of CF lung microbiota.

Evidence and Role for Bacterial Mucin Degradation in Cystic Fibrosis Airway Disease.

Chronic lung infections in cystic fibrosis (CF) patients are composed of complex microbial communities that incite persistent inflammation and airway damage. Despite the high density of bacteria that colonize the lower airways, nutrient sources that sustain bacterial growth in vivo, and how those nutrients are derived, are not well characterized. In this study, we examined the possibility that mucins serve as an important carbon reservoir for the CF lung microbiota. While Pseudomonas aeruginosa was unable to efficiently utilize mucins in isolation, we found that anaerobic, mucin-fermenting bacteria could stimulate the robust growth of CF pathogens when provided intact mucins as a sole carbon source. 16S rRNA sequencing and enrichment culturing of sputum also identified that mucin-degrading anaerobes are ubiquitous in the airways of CF patients. The collective fermentative metabolism of these mucin-degrading communities in vitro generated amino acids and short chain fatty acids (propionate and acetate) during growth on mucin, and the same metabolites were also found in abundance within expectorated sputum. The significance of these findings was supported by in vivo P. aeruginosa gene expression, which revealed a heightened expression of genes required for the catabolism of propionate. Given that propionate is exclusively derived from bacterial fermentation, these data provide evidence for an important role of mucin fermenting bacteria in the carbon flux of the lower airways. More specifically, microorganisms typically defined as commensals may contribute to airway disease by degrading mucins, in turn providing nutrients for pathogens otherwise unable to efficiently obtain carbon in the lung.

WS14.5 What is happening when Pseudomonas aeruginosa grows in a cystic fibrosis lung microbiota?

WS14.5 What is happening when Pseudomonas aeruginosa grows in a cystic fibrosis lung microbiota?

Lung microbiota across age and disease stage in cystic fibrosis.

Understanding the significance of bacterial species that colonize and persist in cystic fibrosis (CF) airways requires a detailed examination of bacterial community structure across a broad range of age and disease stage. We used 16S ribosomal RNA sequencing to characterize the lung microbiota in 269 CF patients spanning a 60 year age range, including 76 pediatric samples from patients of age 4–17, and a broad cross-section of disease status to identify features of bacterial community structure and their relationship to disease stage and age. The CF lung microbiota shows significant inter-individual variability in community structure, composition and diversity. The core microbiota consists of five genera - Streptococcus, Prevotella, Rothia, Veillonella and Actinomyces. CF-associated pathogens such as Pseudomonas, Burkholderia, Stenotrophomonas and Achromobacter are less prevalent than core genera, but have a strong tendency to dominate the bacterial community when present. Community diversity and lung function are greatest in patients less than 10 years of age and lower in older age groups, plateauing at approximately age 25. Lower community diversity correlates with worse lung function in a multivariate regression model. Infection by Pseudomonas correlates with age-associated trends in community diversity and lung function.

Changes in Cystic Fibrosis Airway Microbiota at Pulmonary Exacerbation

In persons with cystic fibrosis (CF), repeated exacerbations of pulmonary symptoms are associated with a progressive decline in lung function. Changes in the airway microbiota around the time of exacerbations are not well understood. To characterize changes in airway bacterial communities around the time of exacerbations and to identify predictors for these changes. DNA prepared from 68 paired baseline and exacerbation sputum samples collected from 28 patients with CF were subjected to barcoded 16S rRNA gene pyrosequencing. Bacterial density was calculated by quantitative PCR. Overall, significant differences in bacterial community diversity and bacterial density between baseline and exacerbation samples were not observed. However, considerable changes in community structures were observed in a subset of patients. In these patients, the dominant taxa and initial level of community diversity were significant predictors of the magnitude of community structure changes at exacerbation. Pseudomonas-dominant communities became more diverse at exacerbation compared with communities with other or no dominant species. The relative abundance of Gemella increased in 24 (83%) of 29 samples at exacerbation and was found to be the most discriminative genus between baseline and exacerbation samples. The magnitude of changes in the CF lung microbiota around the time of exacerbation was found to be largely dependent on community diversity and composition at baseline. Certain genera appear to play important roles in driving change in airway bacterial community composition at exacerbation. Gemella might play a direct role in and/or be a biomarker for pulmonary exacerbation.

Analysis of the Cystic Fibrosis Lung Microbiota via Serial Illumina Sequencing of Bacterial 16S rRNA Hypervariable Regions

The characterization of bacterial communities using DNA sequencing has revolutionized our ability to study microbes in nature and discover the ways in which microbial communities affect ecosystem functioning and human health. Here we describe Serial Illumina Sequencing (SI-Seq): a method for deep sequencing of the bacterial 16S rRNA gene using next-generation sequencing technology. SI-Seq serially sequences portions of the V5, V6 and V7 hypervariable regions from barcoded 16S rRNA amplicons using an Illumina short-read genome analyzer. SI-Seq obtains taxonomic resolution similar to 454 pyrosequencing for a fraction of the cost, and can produce hundreds of thousands of reads per sample even with very high multiplexing. We validated SI-Seq using single species and mock community controls, and via a comparison to cystic fibrosis lung microbiota sequenced using 454 FLX Titanium. Our control runs show that SI-Seq has a dynamic range of at least five orders of magnitude, can classify >96% of sequences to the genus level, and performs just as well as 454 and paired-end Illumina methods in estimation of standard microbial ecology diversity measurements. We illustrate the utility of SI-Seq in a pilot sample of central airway secretion samples from cystic fibrosis patients.

WS20.1 Target minority bacterial population in cystic fibrosis lung microbiota

Staphylococcus aureus is one of the most frequently encountered species in Cystic Fibrosis (CF) lung microbiota. However its frequent presence on agar plates from sputum samples of CF patients likely impaired the culture of other minority bacterial species that may be responsible for lung exacerbations. In order to discover this minority bacterial population, we examined the sputum sample of a CF patient using conventional culture dependent with or without inhibition of S. aureus growth with vancomycin and compare our results to culture independent molecular techniques. Using standard cultures as well as selective media at different physico-chemical conditions, we isolate Staphylococcus aureus in the majority of our culture conditions and media. Interestingly, after pre-incubation of the sample with Vancomycin to inhibit Staphylococcus aureus growth, we isolate new bacterial species (Granulicatella, Streptococcus, Rothia, Lactobacillus and Propionibacterium species), especially Actinomyces radicidentis, a rare bacterial species associated with endodontic infections never described in the context of CF. Using 16S rDNA PCR amplification and sequencing of subsequent clones, we identified Streptococcus, Granulicatella, Rothia, Abiotropha, Peptostreptococcus, Lachnospiraceae and Actinomyces along with S. aureus confirming the culture dependent findings. In conclusion, the use of various bacterial inhibitors to inhibit the growth of the dominant bacteria may help to discover the minority bacterial population that could be new or emerging species in the context of CF.

The Airway Microbiota in Cystic Fibrosis: A Complex Fungal and Bacterial Community—Implications for Therapeutic Management

BackgroundGiven the polymicrobial nature of pulmonary infections in patients with cystic fibrosis (CF), it is essential to enhance our knowledge on the composition of the microbial community to improve patient management. In this study, we developed a pyrosequencing approach to extensively explore the diversity and dynamics of fungal and prokaryotic populations in CF lower airways.Methodology and Principal FindingsFungi and bacteria diversity in eight sputum samples collected from four adult CF patients was investigated using conventional microbiological culturing and high-throughput pyrosequencing approach targeting the ITS2 locus and the 16S rDNA gene. The unveiled microbial community structure was compared to the clinical profile of the CF patients. Pyrosequencing confirmed recently reported bacterial diversity and observed complex fungal communities, in which more than 60% of the species or genera were not detected by cultures. Strikingly, the diversity and species richness of fungal and bacterial communities was significantly lower in patients with decreased lung function and poor clinical status. Values of Chao1 richness estimator were statistically correlated with values of the Shwachman-Kulczycki score, body mass index, forced vital capacity, and forced expiratory volume in 1 s (p = 0.046, 0.047, 0.004, and 0.001, respectively for fungal Chao1 indices, and p = 0.010, 0.047, 0.002, and 0.0003, respectively for bacterial Chao1 values). Phylogenetic analysis showed high molecular diversities at the sub-species level for the main fungal and bacterial taxa identified in the present study. Anaerobes were isolated with Pseudomonas aeruginosa, which was more likely to be observed in association with Candida albicans than with Aspergillus fumigatus.ConclusionsIn light of the recent concept of CF lung microbiota, we viewed the microbial community as a unique pathogenic entity. We thus interpreted our results to highlight the potential interactions between microorganisms and the role of fungi in the context of improving survival in CF.

Assessment of sample handling practices on microbial activity in sputum samples from patients with cystic fibrosis

The aim of this study was to quantitatively and qualitatively assess the effect of sample storage on the metabolically active microbial community found in sputum samples from patients with cystic fibrosis (CF). Sputum samples were collected and split in two equal aliquots one of which was immersed in RNAlater and refrigerated immediately, the second stored at room temperature for 24 h and RNAlater was subsequently added. mRNA was extracted, and RT-PCR-DGGE and qPCR analysis of the bacterial and fungal communities was carried out. Significant differences in the bacterial communities between the two protocols were observed but there were no significant difference seen in the fungal community analyses. Analysis by qPCR demonstrated that room temperature storage gave statistically significant increases in eubacteria and Pseudomonas spp. and a statistically significant decrease in those of Haemophilus influenzae. The analysis of metabolically active microbial communities from CF sputum using molecular techniques indicated that samples should be stored at 4 degrees C upon addition of RNAlater to obtain an accurate depiction of the CF lung microbiota. Also, storing respiratory samples at room temperature may cause an over representation of Pseudomonas aeruginosa and mask the presence of other clinically significant organisms.