The CFTR protein affected by CF is an ion channel that transports chloride and bicarbonate across the epithelial apical membrane. The CF-causing mutations in the CFTR gene result in either complete loss of function (mutation class I), decreased synthesis of CFTR (class V), or defects in protein maturation (class II), channel opening (class III), or ion transport (class IV). The basic defect of CF in epithelial anion transport can be detected in patients with CFTR biomarkers on the epithelium of the sweat gland and the mucosa of the respiratory tract and intestine. We use these CFTR biomarkers to establish the diagnosis of CF or a CFTR-associated disorder when CF is clinically suspected, or to test the efficacy of drugs in clinical trials to see if they attenuate or even compensate for the underlying defect of CF.

Although more than 2000 CF-causing mutations in the CFTR gene are known, the most common mutation p.Phe508del occurs on 70% of all CF chromosomes. p.Phe508del is thus the most common severe mutation in Europe, so that we can use p.Phe508del homozygous CF patients as an example to test which environmental factors and which genetic factors outside the causally affected gene modulate the severity of the clinical picture in a congenital disease. For the studies, we have DNA samples available from the local CF outpatient clinic and from participants in the European Sibling and Twin Study. Modulators are phenotyped in bioassays at the cellular and/or molecular level.

Chronic respiratory tract infections with opportunistic pathogens determine the quality and expectation of life for most patients with CF. Complementary to standard antimicrobial chemotherapy, we are exploring options in animal models to prevent lower respiratory tract infections via local transfer of macrophages, CFTR gene, reprogrammed stem cells or corrected CF host cells.

Pseudomonas aeruginosa lives in soil, fresh and salt water and colonizes plant and animal surfaces. In humans, P. aeruginosa has become one of the most common bacterial pathogens of local infections of the eye, ear, and urinary tract and of life-threatening infections of burn patients and ventilated patients in intensive care units worldwide. Chronic colonization of the lung with P. aeruginosa reduces the prognosis of patients with CF, bronchiectasis or COPD.

The Clinical Research Group has the largest strain collection of P. aeruginosa isolates in the world. We have studied the population biology of P. aeruginosa in environmental and disease habitats and the infectious epidemiology of the pathogen in patients with CF, bronchiectasis, or COPD. Genome sequencing of representatives of the most common clones was used to elucidate the organization and inter- and intraclonal diversity of the core and accessory genomes of P. aeruginosa. Microevolution of P. aeruginosa in the CF lung is studied in genomic analyses and fitness experiments of serial isolates collected semiannually for up to forty years since the beginning of colonization of the respiratory tract. Our current research interest is the evolution and virulence of pandemic clonal lineages that have become a serious global health problem because of their multidrug or even panresistance to Pseudomonas-active anti-infectives.

The Human Microbiome Project has characterized the microbiome of healthy humans in numerous organs, but has left out the lower respiratory tract.  We aim to fill this gap. The 10-100 ng of genomic DNA that can be obtained from nasal lavage, induced sputum, or deep throat swab will be depth sequenced using a high-throughput method. The 107-109 DNA sequences are mapped onto a microbial pangenome of thousands of completely sequenced genomes of yeasts, fungi, DNA viruses, and bacteria and taxonomically classified to the levels of species, clone, or clonal variant. Using the isolated or assembled sequences, microbial communities are characterized in terms of population structure, genome diversity, metabolic potential, and bacterial growth rates. We study the respiratory metagenome of lung-healthy subjects, patients with acute respiratory infections and of patients with chronic lung disease (asthma, COPD, cystic fibrosis, bronchiectasis). The datasets will be searched for the microbial signatures that distinguish chronic lung diseases from each other and differentiate between pulmonary exacerbation and clinically stable condition. Algorithm development will play a central role in the coming years.