Advertisement
Original Article|Articles in Press

Airway bacterial community composition in persons with advanced cystic fibrosis lung disease

Published:January 09, 2023DOI:https://doi.org/10.1016/j.jcf.2023.01.001

      Highlights

      • Although the progression of lung disease in CF has been associated with airway microbial communities with decreased bacterial diversity, a significant minority of individuals with advanced lung disease maintain relatively diverse communities, and these individuals experience greater lung transplant-free survival.
      • Elucidation of the relationship between lung disease and airway bacterial community structure has potential to advance novel strategies to improve clinical outcomes.

      Abstract

      Background

      The progression of lung disease in people with cystic fibrosis (pwCF) has been associated with a decrease in the diversity of airway bacterial communities. How often low diversity communities occur in advanced CF lung disease and how they may be associated with clinical outcomes is not clear, however.

      Methods

      We sequenced a region of the bacterial 16S ribosomal RNA gene to characterize bacterial communities in sputum from 190 pwCF with advanced lung disease (FEV1≤40% predicted), with particular attention to the prevalence and relative abundance of dominant genera. We evaluated relationships between community diversity and clinical outcomes.

      Results

      Although most of the 190 pwCF with advanced lung disease had airway bacterial communities characterized by low diversity with a dominant genus, a considerable minority (40%) did not. The absence of a dominant genus, presence of methicillin-susceptible Staphylococcus aureus, and greater bacterial richness positively correlated with lung function. Higher relative abundance of the dominant genus and greater antimicrobial use negatively correlated with lung function. PwCF with a low diversity community and dominant genus had reduced lung transplant-free survival compared to those without (median survival of 1.6 vs 2.9 years).

      Conclusions

      A considerable proportion of pwCF with advanced lung disease do not have airway bacterial communities characterized by low diversity and a dominant genus and these individuals had better survival. An understanding of the antecedents of low diversity airway communities– and the impact these may have on lung disease trajectory - may provide avenues for improved management strategies.

      Keywords

      Abbreviations:

      16S rRNA (16S ribosomal ribonucleic acid), ASV (amplicon sequence variant), BMI (body mass index), CF (cystic fibrosis), CFTR (cystic fibrosis transmembrane conductance regulator), MRSA (methicillin-resistant Staphylococcus aureus), MSSA (methicillin-sensitive Staphylococcus aureus), pwCF (people with cystic fibrosis), ppFEV1 (percent predicted forced expiratory volume in 1 s)
      To read this article in full you will need to make a payment

      Purchase one-time access:

      Academic & Personal: 24 hour online accessCorporate R&D Professionals: 24 hour online access
      One-time access price info
      • For academic or personal research use, select 'Academic and Personal'
      • For corporate R&D use, select 'Corporate R&D Professionals'

      Subscribe:

      Subscribe to Journal of Cystic Fibrosis
      Already a print subscriber? Claim online access
      Already an online subscriber? Sign in
      Institutional Access: Sign in to ScienceDirect

      References

        • Francoise A.
        • Hery-Arnaud G.
        The microbiome in cystic fibrosis pulmonary disease.
        Genes. 2020; 11: 536
        • Bevivino A.
        • Bacci G.
        • Drevinek P.
        • Nelson M.T.
        • Hoffman L.
        • Mengoni A.
        Deciphering the ecology of cystic fibrosis bacterial communities: towards systems-level integration.
        Trends Mol Med. 2019; 25: 1110-1122
        • Scialo F.
        • Amato F.
        • Cernera G.
        • Gelzo M.
        • Zarrilli F.
        • Comegna M.
        • et al.
        Lung microbiome in cystic fibrosis.
        Life. 2021; 11: 94
        • Huang Y.J.
        • LiPuma J.J.
        The microbiome in cystic fibrosis.
        Clin Chest Med. 2016; 37: 59-67
        • Cuthbertson L.
        • Walker A.W.
        • Oliver A.E.
        • Rogers G.B.
        • Rivett D.W.
        • Hampton T.H.
        • et al.
        Lung function and microbiota diversity in cystic fibrosis.
        Microbiome. 2020; 8: 45
        • Coburn B.
        • Wang P.W.
        • Diaz Caballero J.
        • Clark S.T.
        • Brahma V.
        • Donaldson S.
        • et al.
        Lung microbiota across age and disease stage in cystic fibrosis.
        Sci Rep. 2015; 5: 10241
        • Zhao J.
        • Schloss P.D.
        • Kalikin L.M.
        • Carmody L.A.
        • Foster B.K.
        • Petrosino J.F.
        • et al.
        Decade-long bacterial community dynamics in cystic fibrosis airways.
        Proc Natl Acad Sci U S A. 2012; 109: 5809-5814
        • Boutin S.
        • Graeber S.Y.
        • Stahl M.
        • Dittrich A.S.
        • Mall M.A.
        • Dalpke A.H.
        Chronic but not intermittent infection with Pseudomonas aeruginosa is associated with global changes of the lung microbiome in cystic fibrosis.
        Eur Respir J. 2017; 50
        • Frey D.L.
        • Boutin S.
        • Dittrich S.A.
        • Graeber S.Y.
        • Stahl M.
        • Wege S.
        • et al.
        Relationship between airway dysbiosis, inflammation and lung function in adults with cystic fibrosis.
        J Cyst Fibros. 2021; 20: 754-760
        • Frey D.L.
        • Bridson C.
        • Dittrich S.
        • Graeber S.Y.
        • Stahl M.
        • Wege S.
        • et al.
        Changes in microbiome dominance are associated with declining lung function and fluctuating inflammation in people with cystic fibrosis.
        Front Microbiol. 2022; 13885822
        • Goddard A.F.
        • Staudinger B.J.
        • Dowd S.E.
        • Joshi-Datar A.
        • Wolcott R.D.
        • Aitken M.L.
        • et al.
        Direct sampling of cystic fibrosis lungs indicates that DNA-based analyses of upper-airway specimens can misrepresent lung microbiota.
        Proc Natl Acad Sci U S A. 2012; 109: 13769-13774
        • Sherrard L.J.
        • Einarsson G.G.
        • Johnston E.
        • O'Neill K.
        • McIlreavey L.
        • McGrath S.J.
        • et al.
        Assessment of stability and fluctuations of cultured lower airway bacterial communities in people with cystic fibrosis.
        J Cyst Fibros. 2019; 18: 808-816
        • Boon M.
        • Verleden S.E.
        • Bosch B.
        • Lammertyn E.J.
        • McDonough J.E.
        • Mai C.
        • et al.
        Morphometric analysis of explant lungs in cystic fibrosis.
        Am J Respir Crit Care Med. 2016; 193: 516-526
        • Einarsson G.G.
        • Vanaudenaerde B.M.
        • Spence C.D.
        • Lee A.J.
        • Boon M.
        • Verleden G.M.
        • et al.
        Microbial community composition in explanted cystic fibrosis and control donor lungs.
        Front Cell Infect Microbiol. 2021; 11764585
        • Carmody L.A.
        • Zhao J.
        • Schloss P.D.
        • Petrosino J.F.
        • Murray S.
        • Young V.B.
        • et al.
        Changes in cystic fibrosis airway microbiota at pulmonary exacerbation.
        Ann Am Thorac Soc. 2013; 10: 179-187
        • Caverly L.J.
        • Lu J.
        • Carmody L.A.
        • Kalikin L.M.
        • Shedden K.
        • Opron K.
        • et al.
        Measures of cystic fibrosis airway microbiota during periods of clinical stability.
        Ann Am Thorac Soc. 2019; 16: 1534-1542
        • Zhao J.
        • Carmody L.A.
        • Kalikin L.M.
        • Li J.
        • Petrosino J.F.
        • Schloss P.D.
        • et al.
        Impact of enhanced Staphylococcus DNA extraction on microbial community measures in cystic fibrosis sputum.
        PLoS ONE. 2012; 7: e33127
        • Caverly L.J.
        • Carmody L.A.
        • Haig S.J.
        • Kotlarz N.
        • Kalikin L.M.
        • Raskin L.
        • et al.
        Culture-independent identification of nontuberculous mycobacteria in cystic fibrosis respiratory samples.
        PLoS ONE. 2016; 11e0153876
        • Zhao J.
        • Evans C.R.
        • Carmody L.A.
        • LiPuma J.J.
        Impact of storage conditions on metabolite profiles of sputum samples from persons with cystic fibrosis.
        J Cyst Fibros. 2015; 14: 468-473
        • Cuthbertson L.
        • Rogers G.B.
        • Walker A.W.
        • Oliver A.
        • Hafiz T.
        • Hoffman L.R.
        • et al.
        Time between collection and storage significantly influences bacterial sequence composition in sputum samples from cystic fibrosis respiratory infections.
        J Clin Microbiol. 2014; 52: 3011-3016
        • Cuthbertson L.
        • Rogers G.B.
        • Walker A.W.
        • Oliver A.
        • Hoffman L.R.
        • Carroll M.P.
        • et al.
        Implications of multiple freeze-thawing on respiratory samples for culture-independent analyses.
        J Cyst Fibros. 2015; 14: 464-467
        • Acosta N.
        • Whelan F.J.
        • Somayaji R.
        • Poonja A.
        • Surette M.G.
        • Rabin H.R.
        • et al.
        The evolving cystic fibrosis microbiome: a comparative cohort study spanning 16 years.
        Ann Am Thorac Soc. 2017; 14: 1288-1297
        • McMurdie P.J.
        • Holmes S.
        phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data.
        PLoS ONE. 2013; 8: e61217
        • Wickham H.
        Ggplot2: elegant graphics for data analysis.
        2nd ed. Springer International Publishing, 2016
      1. Oksanen F.J., et al. (2017) Vegan: community ecology package. R package Version 2.4-3. https://CRAN.R-project.org/package=vegan.

        • Nadkarni M.A.
        • Martin F.E.
        • Jacques N.A.
        • Hunter N.
        Determination of bacterial load by real-time PCR using a broad-range (universal) probe and primers set.
        Microbiology. 2002; 148: 257-266
        • R Core Team
        A language and environment for statistical computing.
        R Foundation for Statistical Computing, Vienna, Austria2014 (ISBN 3-900051-07-0. URL)
      2. Therneau, T.M. (2020). A package for survival analysis in R. https://CRAN.R-project.org/package=survival.

        • Carmody L.A.
        • Kalikin L.M.
        • VanDevanter D.R.
        • Li G.
        • Opron K.
        • Simon R.H.
        • et al.
        Changes in airway bacterial communities occur soon after initiation of antibiotic treatment of pulmonary exacerbations in cystic fibrosis.
        J Cyst Fibros. 2022; (Jun 3:S1569-1993(22)00149-7Epub ahead of print)https://doi.org/10.1016/j.jcf.2022.05.011
        • Limoli D.H.
        • Hoffman L.R
        Help, hinder, hide and harm: what can we learn from the interactions between Pseudomonas aeruginosa and Staphylococcus aureus during respiratory infections?.
        Thorax. 2019; 74: 684-692
        • Kitsios G.D.
        • Fitch A.
        • Manatakis D.V.
        • Rapport S.F.
        • Li K.
        • Qin S.
        • et al.
        Respiratory microbiome profiling for etiologic diagnosis of pneumonia in mechanically ventilated patients.
        Front Microbiol. 2018; 9: 1413https://doi.org/10.3389/fmicb.2018.01413