Cystic Fibrosis Microbiology: Optimizing Molecular Diagnostic Approaches

Abstract

Cystic fibrosis (CF) lung infections are naturally polymicrobial, involving complex diverse microbial communities. This dissertation addresses several aspects of CF pathogen detection, and microbial community diversity and composition, using advanced molecular techniques. The focus areas include: (i) development and optimization of a novel cystic fibrosis Ribosomal Intergenic Spacer Analysis (cfRISA) PCR method designed to capture CF pathogens. This chapter evaluated an in-house designed cfRISA PCR method and showed it had better sensitivity and specificity in detecting CF pathogens compared to traditional PCR methods (chapter 3); (ii) comparative analysis of DNA extraction methods (FastPrep vs. Maxwell) for microbial community profiling in CF sputum. Analysis of two sputum DNA extraction methods showed no significant differences between the FastPrep and Maxwell DNA extraction methods on microbiota capture, although FastPrep showed a marginal advantage in capturing overall fungal diversity (chapter 4); (iii) microbiota diversity and taxonomic composition in adults and children with CF. The microbiota profiling through culture independent sequencing revealed significant microbial diversity within the sputum samples of people with CF (pwCF). This analysis emphasised the limitations of conventional culture-based diagnostics and the advantages of molecular techniques in capturing the CF lung diversity (chapter 5 and 6); and (iv) the potential of theraputic agents to alter the CF lung microbiota. It also showed that therapeutics such as cystic fibrosis transmembrane conductance regulator (CFTR) modulators and the novel oligosaccharide, Oligo G, altered the microbiota present in the CF lung (chapter 6 and 7). The implications of these findings suggest that integrating molecular diagnostics into routine clinical practice could substantially improve the management of CF lung infection. It potentially can offer a more personalized approach to CF management based on microbial community profiles. Ultimately, this research contributes to a deeper understanding of the CF lung microbiota diversity and composition, and advocates a shift towards more advanced diagnostic molecular approaches and different respiratory samples to be used in clinical practice.