Metagenomic assessment of sputum microbiota from patients with chronic pulmonary diseases

Abstract number: P1316

Friaza V., de la Horra C., Ayala G., Máiz L., Dapena J., Canton R., Calderon E., del Campo R.

Objective: To identify the main features of microbiota associated with cystic fibrosis (CF) and bronchiectasis, two models of chronic lung diseases, using a non-culture microbiological approach.

Methods: Sputum samples (one per patient) were collected from 15 CF-patients and from 15 patients with non-CF bronchiectasis. All patients presented a stable clinical status without acute exacerbations. Total DNA from each sputum sample was obtained manually using a phenol/chloroform protocol and diluted up to 50 ng/ml. PCR-DGGE technique was performed in all samples using universal primers for Bacterial Domain based on 16S rRNA conserved regions. Amplicons were separated in vertical electrophoresis polyacrylamide gels (8%) at 60°C; with a urea-formamide denaturating gel gradient of 30–45%. Gels were visualised with ethidium bromide; common and unique bands were excised, re-amplified and sequenced in order to assign bacterial species identification. Similarities among the electrophoretic band patterns were analyzed using the Phoretrix 5.0 software^® and dendrograms were constructed based on the Dice coefficient.

Results: All CF-patient samples presented a marked band of Pseudomonas aeruginosa, which was undetectable in those patients with bronchiectasis. On the other hand, several band patterns were common to both groups. As expected, different species corresponded to bacteria habitually found in sputum samples (Haemophilus influenzae, Stenotrophomonas maltophilia, Moraxella spp., Actinomyces odontolyticus.) although several sequences corresponded to uncultured bacterium related with Streptococcus, Actinobacterium or Neisseria groups. Interestingly, environmental organisms such as Pseudomonas synxantha, Ochrobactrum anthropi, Rothia amarae, Rothia mucilaginosa, Phycicoccus dokdonensis, or Arthrobacter spp. were detected.

Conclusion: Metagenomic tools are useful to identify the microbiota present in patients with chronic pulmonary diseases. Moreover, we were able to detect uncultured and environmental bacteria in sputa from CF and non-CF bronchiectasis patients that have not been previously described in this type of samples.