Background and objectives

Modulator therapy in cystic fibrosis (CF) has led to a substantial clinical improvement of the CF patient population. However, there is currently lack of data and no consensus regarding the long-term impact of modulators on the lung microbiome and infections. Studies are often limited by the lack microbiological resolution, focus on single pathogens and none studied the Belgian CF population. Importantly, no studies investigated impact on the fungal lung microbiome, although also of importance in CF. Therefore, we aim to follow-up the lung bacterial and fungal microbiome in the era of modulator therapy.

Also, despite the success of modulators, there is no evidence so far that patients can stop or alter antibiotics to treat chronic lung infections or as prophylaxis. This is especially since chronic infections are common in CF and may not disappear with current modulators. Increasingly, these infections are caused by multi-drug resistant bacterial pathogens, such as Pseudomonas aeruginosa, Staphylococcus aureus and Achromobacter xylosoxidans, sometimes impossible to eradicate. Phages are viruses that are able to kill these bacterial pathogens and a most promising alternative. Now, the most effective phages against a pathogen are selected in vitro but this does not reflect the in vivo CF-lung. Our recent ex vivo model for phage selection became unfeasible because the limited volume of sputa produced due to modulator therapy. Therefore, we aim to establish a new innovative phage selection method to improve phage therapy.

Methodology

During routine follow-up of patients, over a three-year period, we will collect sputa. The fungal and bacterial microbiome will be assessed by 16S and ITS-2 metataxonomic Nanopore sequencing, respectively, and compared with baseline data we recently analyzed. To improve the phage selection procedure, we will first culture sputa for Achromobacter xylosoxidans, Pseudomonas aeruginosa and Staphylococcus aureus and assess the whole- genome sequence of these pathogens. We will then use an innovative in-house developed ‘PMD4U’ assay to screen for effective phages against pathogens. Using a 3D-lung-biofilm model that resembles the in vivo CF-lung, we will further select for those phages that are considered most effective in vivo. An online inventory will be designed for the CF-community to share pathogen and phage genomes as well as phage susceptibility patterns.

Outcome

We expect to improve our phage therapy protocol and offer alternatives to antibiotics for the treatment of multi- drug resistant infections. Online sharing of data and resources will catalyze entry of phage therapy as part of routine care in CF. Our metagenomic analysis will shed clarity composition of the fungal and bacterial CF-lung microbiome in the era of modulators and help the management of infections.