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Project

Insights into viral and bacterial colonisation of the lower respiratory tract in cystic fibrosis patients through metagenomic sequencing and multiplex qPCR.

Cystic fibrosis (CF) causes impaired mucociliary clearance in the airways and stasis of mucus, leading to chronic infection and inflammation. Increasing evidence suggests a role for the entire microbial community to orchestrate the course of airway infections in CF, including beneficial microorganisms with anti-pathogenic and immunomodulatory properties. It is thus important to perform high resolution microbiome sequencing of the entire respiratory microbiome that can shed light on the interplay of a wide range of microorganisms inhabiting the airways in CF patients. Most of the current CF microbiome studies are done using 16S amplicon sequencing. However, 16S amplicon sequencing is not always able to identify up to the bacterial species or strain level. This poses an important research gap since pathogenicity and probiotic potential of microbiota members are often expressed at strain level. Shotgun sequencing is recently emerging as an alternative for respiratory microbiome sequencing and has the advantage to detect bacterial taxa at species or even strain level and potentially also gain insight into the functional genes within the respiratory microbiome. In contrast to 16S amplicon sequencing, the shotgun method implies sequencing of all DNA within a sample, both human and microbial. Finally, no viruses can be identified using the 16S amplicon sequencing technique that specifically focuses on bacteria. This is important as respiratory exacerbations, especially in young children, are viral induced. We aim to implement shotgun sequencing in comparison with 16S rRNA amplicon sequencing to gain detailed insights into the lower respiratory tract microbiome in CF and its link with viruses. To reach this goal, we aim to (1) optimize and implement shotgun metagenomic sequencing for LRT sputum samples in parallel with 16S sequencing, and (2) align the sequencing data with multiplex qPCR for virus detection.
Date:1 Apr 2022 →  31 Mar 2023
Keywords:MICROBIOME, MUCOVISCIDOSIS
Disciplines:Microbiome, Paediatrics