The airway microbiota in cystic fibrosis: a complex fungal and bacterial community--implications for therapeutic management

Abstract

Background: Given 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 findings: Fungi 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.

Conclusions: In 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.

Figure 1. Rarefaction curves.

These curves are representing the numbers of OTUs with respect to the number of pyrosequence reads obtained from each patient at different sampling times and using the two set of primers targeting prokaryotic 16S rDNA (A) and fungal ITS2 (B) loci.

Figure 2. Relation between species richness and clinical status (A) or lung function (B).

Total richness of prokaryotic and fungal communities from each patient-sample was expressed using the Chao1 richness estimator; each spot size is proportional to the corresponding Chao1 value. The clinical status is expressed as S-K score and BMI in Figure 2A, while lung function is expressed as FEV1 and FVC values in Figure 2B. Given to the absence of S-K score value from Patient 2-sample 2 (Table 1), this spot is missing in Figure 2A. Bacterial and fungal Chao1 values corresponding to Patient 1, Patient 2, Patient 3, and Patient 4 are represented in blue-, green-, red- and yellow-edged spots, respectively. Dark and light colour intensity is corresponding to the first and second sampling dates of each patient, respectively. Dark grey and light grey are corresponding to fungal and bacterial Chao1 richness values, respectively.