Analysis of Lung Microbiota in Bronchoalveolar Lavage, Protected Brush and Sputum Samples from Subjects with Mild-To-Moderate Cystic Fibrosis Lung Disease

Hogan, Deborah A.; Willger, Sven D.; Dolben, Emily L.; Hampton, Thomas H.; Stanton, Bruce A.; Morrison, Hilary G.; Sogin, Mitchell L.; Czum, Julianna M.; Ashare, Alix

doi:10.1371/journal.pone.0149998

Cited by 112 publications

(107 citation statements)

References 63 publications

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“…Based on these results, we focused our community modeling efforts on predicting the infrequent dominance of the pathogens Enterobacteriaceae , Burkholderia and Achromobacter , and the heterogeneity in the abundances of Pseudomonas, Streptococcus, Prevotella and Haemophilus across the remaining samples. Pseudomonas , Streptococcus and Prevotella have been found by directly sampling the lung of CF patients via bronchoalveolar lavage (38), while Haemophilus is a widely-accepted CF pathogen (7). The other 10 genera (Table 1) were maintained in the model to simulate competition/cooperation with the more dominant species and to determine if the relatively low abundances of these genera could be predicted.…”

Section: Resultsmentioning

confidence: 99%

Metabolic Modeling of Cystic Fibrosis Airway Communities Predicts Mechanisms of Pathogen Dominance

Henson

Orazi

Phalak

et al. 2019

Preprint

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5Cystic fibrosis (CF) is a fatal genetic disease characterized by chronic lung infections due to aberrant 1 6 mucus production and the inability to clear invading pathogens. The traditional view that CF infections 1 7 are caused by a single pathogen has been replaced by the realization that the CF lung usually is colonized 1 8 by a complex community of bacteria, fungi and viruses. To help unravel the complex interplay between 1 9 the CF lung environment and the infecting microbial community, we developed a community metabolic 2 0 CF lung metabolomics and 16S sequencing could provide important insights into disease progression and 3 2 treatment efficacy. 3 3 Importance 3 4Cystic fibrosis (CF) is a genetic disease in which chronic airway infections and lung inflammation result 3 5 in respiratory failure. CF airway infections are usually caused by bacterial communities that are difficult 3 6 to eradicate with available antibiotics. Using species abundance data for clinically stable adult CF patients 3 7 assimilated from three published studies, we developed a metabolic model of CF airway communities to 3 8 better understand the interactions between bacterial species and between the bacterial community and the 3 9 lung environment. Our model predicted that clinically-observed CF pathogens could establish dominance 4 0 over other community members across a range of lung nutrient conditions. Heterogeneity of species 4 1 abundances across 75 patient samples could be predicted by assuming that sample-to-sample 4 2 heterogeneity was attributable to random variations in the CF nutrient environment. Our model 4 3 predictions provide new insights into the metabolic determinants of pathogen dominance in the CF lung 4 4 and could facilitate the development of improved treatment strategies. 4 5 4 6shaping community composition and behavior, and the impact of community composition on the efficacy 7 1 of antibiotic treatment regimens. 7 2In silico metabolic modeling has emerged as a powerful approach for analyzing complex microbial 7 3 communities by integrating genome-scale reconstructions of single-species metabolism within 7 4 mathematical descriptions of metabolically interacting communities (11, 12). Modeled species 7 5 interactions typically include competition for host-derived nutrients and cross-feeding of secreted 7 6 byproducts such as organic acids, alcohols and amino acids between species (13, 14). Due to challenges 7 7 in developing manually curated reconstructions of poorly studied species, including those present in the 7 8 CF lung, most in silico community models have been restricted to ~5 microbial species (15-17) and fail to 7 9adequately cover the diversity of in vivo communities. This limitation can be overcome in bacterial 8 0 communities by using semi-curated reconstructions developed through computational pipelines such as 8 1 the ModelSeed (18), AGORA (19) and other methods (20). Given the availability of suitable single-strain 8 2 metabolic reconstructions, a number of alternative methods have been develo...

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Section: Resultsmentioning

confidence: 99%

Metabolic Modeling of Cystic Fibrosis Airway Communities Predicts Mechanisms of Pathogen Dominance

Henson

Orazi

Phalak

et al. 2019

Preprint

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“…Whilst all genera found have been previously described in the blood (see references), the predominance of Achromobacter, which is not classically associated with the blood microbiome, warrants further consideration. Indeed, Achromobacter has been detected abundantly in the lower respiratory tract of healthy mice 45 , humans (HPM airway dataset), and in various respiratory conditions 46,47 . Furthermore, no Achromobacter was detected in our experimental control reactions suggesting that its presence is not the result of experimental contamination.…”

Section: Resultsmentioning

confidence: 99%

Multi-Method Characterisation of the Human Circulating Microbiome

Whittle

Leonard

Harrison

et al. 2018

Preprint

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“…Based on current evidence that multiple Streptococcus species inhabit the CF lung (8, 32) and influence patient health (5, 6, 8–11, 15, 16), we sought to determine whether the observed enhancement of Streptococcus viable counts in coculture with P. aeruginosa may be more broadly generalized to other streptococci, including the Streptococcus milleri group (SMG), which has been implicated in CF-related exacerbations (5, 6, 8, 15). To assess the ability of P. aeruginosa to promote multiple Streptococcus spp., we cocultured P. aeruginosa PAO1 with 6 SMG isolates and 8 oral Streptococcus spp.…”

Section: Resultsmentioning

confidence: 99%

“…Pseudomonas aeruginosa is the dominant microorganism (>50% relative abundance) in the lungs of ~45% of adults patients with CF (12), is cultured from >80% of these patients (13), and is the predominant microbe in the lung at end stage disease (14). P. aeruginosa and streptococci have been found to co-colonize CF patients (5, 6, 8, 15, 16), but the polymicrobial interactions that occur between these organisms are not well studied. Previous studies investigating interactions between P. aeruginosa and Streptococcus spp.…”

Section: Introductionmentioning

confidence: 99%

Pseudomonas aeruginosaCan Inhibit Growth of Streptococcal Species via Siderophore Production

Scott

Filkins

et al. 2018

Preprint

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Cystic Fibrosis (CF) is a genetic disease that causes patients to accumulate thick, dehydrated mucus in the lung and develop chronic, polymicrobial infections due to reduced mucociliary clearance. These chronic polymicrobial infections and subsequent decline in lung function are significant factors in the morbidity and mortality of CF. Pseudomonas aeruginosa and Streptococcus spp. are among the most prevalent organisms in the CF lung; the presence of P. aeruginosa correlates with lung function decline and the Streptococcus milleri group (SMG), a subgroup of the viridans streptococci, is associated with exacerbations in patients with CF. Here we characterize the interspecies interactions that occur between these two genera. We demonstrated that multiple P. aeruginosa laboratory strains and clinical CF isolates promote the growth of multiple SMG strains and oral streptococci in an in vitro coculture system. We investigated the mechanism by which P. aeruginosa enhances growth of streptococci by screening for mutants of P. aeruginosa PA14 unable to enhance Streptococcus growth, and we identified the P. aeruginosa pqsL::TnM mutant, which failed to promote growth of S. constellatus and S. sanguinis. Characterization of the P. aeruginosa ΔpqsL mutant revealed that this strain cannot promote Streptococcus growth. Our genetic data and growth studies support a model whereby the P. aeruginosa ΔpqsL mutant overproduces siderophores, and thus likely outcompetes Streptococcus sanguinis for limited iron. We propose a model whereby competition for iron represents one important means of interaction between P. aeruginosa and Streptococcus spp.ImportanceCystic fibrosis (CF) lung infections are increasingly recognized for their polymicrobial nature. These polymicrobial infections may alter the biology of the organisms involved in CF-related infections, leading to changes in growth, virulence and/or antibiotic tolerance, and could thereby affect patient health and response to treatment. In this study, we demonstrate interactions between P. aeruginosa and streptococci using a coculture model, and show that one interaction between these microbes is likely competition for iron. Thus, these data indicate that one CF pathogen may influence the growth of another and add to our limited knowledge of polymicrobial interactions in the CF airway.

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Analysis of Lung Microbiota in Bronchoalveolar Lavage, Protected Brush and Sputum Samples from Subjects with Mild-To-Moderate Cystic Fibrosis Lung Disease

Cited by 112 publications

References 63 publications

Metabolic Modeling of Cystic Fibrosis Airway Communities Predicts Mechanisms of Pathogen Dominance

Metabolic Modeling of Cystic Fibrosis Airway Communities Predicts Mechanisms of Pathogen Dominance

Multi-Method Characterisation of the Human Circulating Microbiome

Pseudomonas aeruginosaCan Inhibit Growth of Streptococcal Species via Siderophore Production

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