50 Microbiological characterization of patients in Lisbon cystic fibrosis centre (original) (raw)
Related papers
2019
Although the cystic fibrosis (CF) lung microbiome has been characterized in several studies, little is still known about the functions harboured by those bacteria, and how they change with disease status and antibiotic treatment. The aim of this study was to investigate the taxonomic and functional temporal dynamics of airways microbiome in a cohort of CF patients. Multiple sputum samples were collected over 15 months from 22 patients with chronic P. aeruginosa infection, for a total of 79 samples. DNA extracted from samples was subjected to shotgun metagenomic sequencing allowing either strain-level taxonomic profiling and assessment of the functional metagenomic repertoire. High inter-patient taxonomic heterogeneity was found with short-term compositional changes during exacerbations and following antibiotic treatment. Each patient exhibited distinct sputum microbial communities at the taxonomic level, and strain-specific colonization of traditional CF pathogens, including P. aeruginosa, and emerging pathogens. Sputum microbiome was found to be extraordinarily resilient following antibiotic treatment, with rapid recovery of taxa and metagenome-associated gene functions. In particular, a large core set of genes, including antibiotic resistance genes, were shared across patients despite observed differences in clinical status or antibiotic treatment, and constantly detected in the lung microbiome of all subjects independently from known antibiotic exposure, suggesting an overall microbiome-associated functions stability despite taxonomic fluctuations of the communities. IMPORTANCE While the dynamics of CF sputum microbial composition were highly patientspecific, the overall sputum metagenome composition was stable, showing a high resilience along time and antibiotic exposure. The high degree of redundancy in the CF lung microbiome could testifies ecological aspects connected to the disease that were never considered so far, as the large core-set of genes shared between patients despite observed differences in clinical status or antibiotic
Deciphering the Ecology of Cystic Fibrosis Bacterial Communities: Towards Systems-Level Integration
Trends in Molecular Medicine, 2019
Despite over a decade of cystic fibrosis (CF) microbiome research, much remains to be learned about the overall composition, metabolic activities, and pathogenicity of the microbes in CF airways, limiting our understanding of the respiratory microbiome's relation to disease. Systemslevel integration and modeling of host-microbiome interactions may allow us to better define the relationships between microbiological characteristics, disease status, and treatment response. In this way, modeling could pave the way for microbiome-based development of predictive models, individualized treatment plans, and novel therapeutic approaches, potentially serving as a paradigm for approaching other chronic infections. In this review, we describe the challenges facing this effort and propose research priorities for a systems biology approach to CF lung disease. The CF Microbiota: Where Are We Now? CF (OMIM 219700) is the most common life-shortening Mendelian disease in the white populations of Europe and North America, with an incidence of approximately one in 2500-6000 live births and a prevalence of more than 70 000 people living with CF worldwide [1,2]. Disease is caused by mutations in the CF transmembrane conductance regulator (cftr) gene, which encodes an anion channel (CFTR) found in both secretory and absorbing epithelia. This defect results in abnormal sodium, chloride, and bicarbonate transport across these epithelia, altering the composition of secretions in the lung, gastrointestinal tract, pancreas, biliary ducts, and other secretory glands. In the airways, absent or dysfunctional CFTR results in thick and tenacious mucus that compromises mucociliary clearance. This condition predisposes individuals to chronic bacterial infections and airway inflammation. During chronic infection, bacterial pathogens adapt to the microenvironment of CF airways [3,4], such as a thickened mucus layer and steep hypoxic gradients [5,6], possibly also modulating virulence mechanisms and resulting in damage to the airways and consequent chronic lung disease. Bacterial lung infections are associated with reduced quality and length of life in CF (median predicted survival age of 43.6 years between 2013 and 2017, according to the Annual Data Report 2017 of US Patient Registry Data [7]). These infections are key drivers of a pathophysiological cascade that leads to progressive and irreversible airway damage [8]. Affected individuals consistently maintain high bacterial loads in their airways both during periods of clinical stability and episodic increases in symptoms known as pulmonary exacerbations (PEx), (see Glossary). Standard clinical microbiology of CF, both during stability and PEx, usually identifies a relatively low number of bacterial species that are often thought to be important for driving PEx (Table 1), occasionally also including nontuberculous mycobacteria (NTM) and fungi, such as Candida spp., Aspergillus spp., and Scedosporium spp. [9,10]. Subsequent studies utilizing culture-independent analysis demonstrated that a complex mix of bacteria, fungi, and viruses form the airway microbiota (i.e., the communities of microorganisms that inhabit a given environment) of chronically infected individuals with CF [11]. Pioneering studies by Rogers and colleagues [12,13] identified bacterial species not previously associated with CF airways in many CF sputum samples, expanding the list of potential CF pathogens and chronic airway colonizers, and establishing the polymicrobial nature of most CF respiratory infections (Table 1). Research during the past decade using next-generation sequencing confirmed and broadened this list of CF
Microbiome, 2013
Background: Cystic fibrosis (CF) is caused by inherited mutations in the cystic fibrosis transmembrane conductance regulator gene and results in a lung environment that is highly conducive to polymicrobial infection. Over a lifetime, decreasing bacterial diversity and the presence of Pseudomonas aeruginosa in the lung are correlated with worsening lung disease. However, to date, no change in community diversity, overall microbial load or individual microbes has been shown to correlate with the onset of an acute exacerbation in CF patients. We followed 17 adult CF patients throughout the course of clinical exacerbation, treatment and recovery, using deep sequencing and quantitative PCR to characterize spontaneously expectorated sputum samples Results: We identified approximately 170 bacterial genera, 12 of which accounted for over 90% of the total bacterial load across all patient samples. Genera abundant in any single patient sample tended to be detectable in most samples. We found that clinical stages could not be distinguished by absolute Pseudomonas aeruginosa load, absolute total bacterial load or the relative abundance of any individual genus detected, or community diversity. Instead, we found that the microbial structure of each patient's sputum microbiome was distinct and resilient to exacerbation and antibiotic treatment.
Thorax, 2012
Background Culture-independent analysis of the respiratory secretions of people with cystic fibrosis (CF) has identified many bacterial species not previously detected using culture in this context. However, little is known about their clinical significance or persistence in CF airways. Methods The authors characterised the viable bacterial communities in the sputum collected from 14 patients at monthly intervals over 1 year using a molecular community profiling techniquedterminal restriction fragment length polymorphism. Clinical characteristics were also collected, including lung function and medications. Ecological community measures were determined for each sample. Microbial community change over time within subjects was defined using ecological analytical tools, and these measures were compared between subjects and to clinical features. Results Bacterial communities were stable within subjects over time but varied between subjects, despite similarities in clinical course. Antibiotic therapy temporarily perturbed these communities which generally returned to pretreatment configurations within 1 month. Species usually considered CF pathogens and those not previously regarded as such exhibited similar patterns of persistence. Less diverse sputum bacterial communities were correlated to lung disease severity and relative abundance of Pseudomonas aeruginosa. Conclusion Whilst not true in all cases, the microbial communities that chronically infect the airways of patients with CF can vary little over a year despite antibiotic perturbation. The species present tended to vary more between than within subjects, suggesting that each CF airway infection is unique, with relatively stable and resilient bacterial communities. The inverse relationship between community richness and disease severity is similar to findings reported in other mucosal infections.
PloS one, 2013
Chronic polymicrobial infections of the lung are the foremost cause of morbidity and mortality in cystic fibrosis (CF) patients. The composition of the microbial flora of the airway alters considerably during infection, particularly during patient exacerbation. An understanding of which organisms are growing, their environment and their behaviour in the airway is of importance for designing antibiotic treatment regimes and for patient prognosis. To this end, we have analysed sputum samples taken from separate cohorts of CF and non-CF subjects for metabolites and in parallel, and we have examined both isolated DNA and RNA for the presence of 16S rRNA genes and transcripts by high-throughput sequencing of amplicon or cDNA libraries. This analysis revealed that although the population size of all dominant orders of bacteria as measured by DNA-and RNA-based methods are similar, greater discrepancies are seen with less prevalent organisms, some of which we associated with CF for the first time. Additionally, we identified a strong relationship between the abundance of specific anaerobes and fluctuations in several metabolites including lactate and putrescine during patient exacerbation. This study has hence identified organisms whose occurrence within the CF microbiome has been hitherto unreported and has revealed potential metabolic biomarkers for exacerbation.
PLOS ONE, 2016
Chronic airway infection is a hallmark feature of cystic fibrosis (CF) disease. In the present study, sputum samples from CF patients were collected and characterized by 16S rRNA gene-targeted approach, to assess how lung microbiota composition changes following a severe decline in lung function. In particular, we compared the airway microbiota of two groups of patients with CF, i.e. patients with a substantial decline in their lung function (SD) and patients with a stable lung function (S). The two groups showed a different bacterial composition, with SD patients reporting a more heterogeneous community than the S ones. Pseudomonas was the dominant genus in both S and SD patients followed by Staphylococcus and Prevotella. Other than the classical CF pathogens and the most commonly identified non-classical genera in CF, we found the presence of the unusual anaerobic genus Sneathia. Moreover, the oligotyping analysis revealed the presence of other minor genera described in CF, highlighting the polymicrobial nature of CF infection. Finally, the analysis of correlation and anti-correlation networks showed the presence of antagonism and ecological independence between members of Pseudomonas genus and the rest of CF airways microbiota, with S patients showing a more interconnected community in S patients than in SD ones. This population structure suggests a higher resilience of S microbiota with respect to SD, which in turn may hinder the potential adverse impact of aggressive pathogens (e.g. Pseudomonas). In conclusion, our findings shed a new light on CF airway microbiota ecology, improving current knowledge about its composition and polymicrobial interactions in patients with CF.
Lung microbiota across age and disease stage in cystic fibrosis
Scientific Reports, 2015
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. Cystic fibrosis (CF) is characterized by recurrent airway infection, inflammation and progressive decline in lung function. Infection with key organisms such as Pseudomonas aeruginosa and Burkholderia cepacia complex (Bcc) has been associated with the frequent exacerbations of airway dysfunction and progressive functional decline that are the hallmarks of the disease 1-3. Over the last decade, cross-sectional and longitudinal studies of bacterial taxa using culture-independent microbial detection methods such as terminal restriction fragment length polymorphism (T-RFLP) and 16S rRNA gene sequencing, have identified polymicrobial communities in the airways of CF patients that exceed the complexity captured by traditional culture 4-13. Significant heterogeneity in bacterial community composition has been demonstrated within groups of clinically similar patients 5-7. Although the abundance of individual taxa (such as Gemella spp. and the Streptococcus anginosus group), ecological diversity, and community stability are potentially associated with disease status 8,10,14 , no single static or dynamic metric or bacterial taxon has emerged that consistently explains the heterogeneity of disease within otherwise similar hosts. Culture-based methods have demonstrated the clinical significance of infection with pathogens such as P. aeruginosa. Molecular methods have demonstrated that not only their presence or absence, but also
PloS one, 2015
Cystic fibrosis (CF) is a genetic disease resulting in chronic polymicrobial infections of the airways and progressive decline in lung function. To gain insight into the underlying causes of severe lung diseases, we aimed at comparing the airway microbiota detected in sputum of CF patients with stable lung function (S) versus those with a substantial decline in lung function (SD). Microbiota composition was investigated by using culture-based and culture-independent methods, and by performing multivariate and statistical analyses. Culture-based methods identified some microbial species associated with a worse lung function, i.e. Pseudomonas aeruginosa, Rothia mucilaginosa, Streptococcus pneumoniae and Candida albicans, but only the presence of S. pneumoniae and R. mucilaginosa was found to be associated with increased severe decline in forced expiratory volume in 1 second (FEV1). Terminal-Restriction Fragment Length Polymorphism (T-RFLP) analysis revealed a higher bacterial diversit...
Approaches to analyse dynamic microbial communities such as those seen in cystic fibrosis lung
Human Genomics, 2009
Microbial communities play vital roles in many aspects of our lives, although our understanding of microbial biogeography and community profiles remains unclear. The number of microbes or the diversity of the microbes, even in small environmental niches, is staggering. Current microbiological methods used to analyse these communities are limited, in that many microorganisms cannot be cultured. Even for the isolates that can be cultured, the expense of identifying them definitively is much too high to be practical. Many recent molecular technologies, combined with bioinformatic tools, are raising the bar by improving the sensitivity and reliability of microbial community analysis. These tools and techniques range from those that attempt to understand a microbial community from their length heterogeneity profiles to those that help to identify the strains and species of a random sampling of the microbes in a given sample. These technologies are reviewed here, using the microbial communities present in the lungs of cystic fibrosis patients as a paradigm.
mSystems, 2019
Microbial infections are now recognized to be polymicrobial and personalized in nature. Comprehensive analysis and understanding of the factors underlying the polymicrobial and personalized nature of infections remain limited, especially in the context of the host. By visualizing microbiomes and metabolomes of diseased human lungs, we reveal how different the chemical environments are between hosts that are dominated by the same pathogen and how community interactions shape the chemical environment or vice versa. We highlight that three-dimensional organ mapping methods represent hypothesis-building tools that allow us to design mechanistic studies aimed at addressing microbial responses to other microbes, the host, and pharmaceutical drugs.