Introduction: Cystic fibrosis (CF) is a life-shortening genetic disorder in Australians leading, particularly, to chronic lung disease, causing the highest rate of mortality. It remains unclear how microbes can infect CF airways and the poor response by the immune response. Culture methods for pathogen identification are laborious and insensitive to microbial communities and new methods should be used.
Methods: This study performed metagenomic sequencing using short (Illumina) and long reads (ONT) platforms in CF sputa of 6 patients, from whom were collected up to 4 samples while they were under antibiotic treatment. Due to human DNA contamination (~99%) in sputa, an enriching microbial DNA step using saponin was used and genomes were reconstructed de novo using different hybrid assemblies.
Results: Pseudomonas aeruginosa or Stenotrophomonas maltophilia and Staphylococcus aureus were detected as the most abundant pathogens, which was consistent with culture results. All 6 patients had recurrent infections with the same strain of pathogens a few weeks after the end of the treatment, proving the inefficiency of the treatment. This was confirmed by de novo assembly and from real-time analysis (Sketchy) of ONT data. In addition, commensal microbes (e.g. Prevotella sp.) also reported pathogenic, as well as antimicrobial resistance genes and strain mixtures within species were identified.
Conclusions: Our results provide exciting data showing that sequencing is a powerful method for characterizing microbial populations in CF airways. Real-time sequencing helps to identify complex samples leading to a faster diagnose to inform patients’ treatment, leaving time-consuming cultures fall behind. We foresee the usage of ONT technology in the clinics, in the near future, to help doctors in treatments’ guidance in a quick (less than 1 day from sample collection to results) and effective way, not only for cystic fibrosis lung disease, but for all types of infections (e.g. sepsis).