Polymorphonuclear leucocytes consume oxygen in sputum from chronic Pseudomonas aeruginosa pneumonia in cystic fibrosis.

BACKGROUND: Chronic lung infection with Pseudomonas aeruginosa is the most severe complication for patients with cystic fibrosis (CF). This infection is characterised by endobronchial mucoid biofilms surrounded by numerous polymorphonuclear leucocytes (PMNs). The mucoid phenotype offers protection against the PMNs, which are in general assumed to mount an active respiratory burst leading to lung tissue deterioration. An ongoing respiratory burst by the PMNs has, however, not been demonstrated previously in endobronchial secretions from chronically infected patients with CF. OBJECTIVE: Based on the accumulating evidence for depletion of molecular oxygen (O(2)) in the mucus in infected CF bronchi, it was hypothesised that the O(2) depletion in the mucus in infected CF bronchi may be accelerated by the respiratory burst of the PMNs due to the reduction of O(2) to the superoxide anion (O(-)(2)) by the phagocyte NADPH oxidase (Phox). METHODS: Methods were established to isolate the O(2) consumption by the respiratory burst from aerobic respiration in freshly expectorated sputum from chronically infected patients with CF. RESULTS: Inhibition of the Phox with diphenylene iodonium (DPI) delayed O(2) depletion, nearly abolished staining of O(-)(2)-producing PMNs with hydroethidine and inhibited the rapid luminol-enhanced chemiluminescence in sputum. Furthermore, the total O(2) consumption was correlated to the concentration of PMNs in the sputum samples. CONCLUSION: The results demonstrate that CF sputum contains PMNs with an active consumption of O(2) for O(-)(2) production and suggest that the respiratory burst is ongoing and causes accelerated O(2) depletion due to formation of O(-)(2) in the lungs of chronically infected patients with CF.

Antibiotic resistance in Pseudomonas aeruginosa strains with increased mutation frequency due to inactivation of the DNA oxidative repair system.

The chronic Pseudomonas aeruginosa infection of the lungs of cystic fibrosis (CF) patients is characterized by the biofilm mode of growth and chronic inflammation dominated by polymorphonuclear leukocytes (PMNs). A high percentage of P. aeruginosa strains show high frequencies of mutations (hypermutators [HP]). P. aeruginosa is exposed to oxygen radicals, both those generated by its own metabolism and especially those released by a large number of PMNs in response to the chronic CF lung infection. Our work therefore focused on the role of the DNA oxidative repair system in the development of HP and antibiotic resistance. We have constructed and characterized mutT, mutY, and mutM mutants in P. aeruginosa strain PAO1. The mutT and mutY mutants showed 28- and 7.5-fold increases in mutation frequencies, respectively, over that for PAO1. These mutators had more oxidative DNA damage (higher levels of 7,8-dihydro-8-oxodeoxyguanosine) than PAO1 after exposure to PMNs, and they developed resistance to antibiotics more frequently. The mechanisms of resistance were increased beta-lactamase production and overexpression of the MexCD-OprJ efflux-pump. Mutations in either the mutT or the mutY gene were found in resistant HP clinical isolates from patients with CF, and complementation with wild-type genes reverted the phenotype. In conclusion, oxidative stress might be involved in the development of resistance to antibiotics. We therefore suggest the possible use of antioxidants for CF patients to prevent the development of antibiotic resistance.

Maximum Likelihood based comparison of the specific growth rates for P. aeruginosa and four mutator strains.

The specific growth rate for P. aeruginosa and four mutator strains mutT, mutY, mutM and mutY-mutM is estimated by a suggested Maximum Likelihood, ML, method which takes the autocorrelation of the observation into account. For each bacteria strain, six wells of optical density, OD, measurements are used for parameter estimation. The data is log-transformed such that a linear model can be applied. The transformation changes the variance structure, and hence an OD-dependent variance is implemented in the model. The autocorrelation in the data is demonstrated, and a correlation model with an exponentially decaying function of the time between observations is suggested. A model with a full covariance structure containing OD-dependent variance and an autocorrelation structure is compared to a model with variance only and with no variance or correlation implemented. It is shown that the model that best describes data is a model taking into account the full covariance structure. An inference study is made in order to determine whether the growth rate of the five bacteria strains is the same. After applying a likelihood-ratio test to models with a full covariance structure, it is concluded that the specific growth rate is the same for all bacteria strains. This study highlights the importance of carrying out an explorative examination of residuals in order to make a correct parametrization of a model including the covariance structure. The ML method is shown to be a strong tool as it enables estimation of covariance parameters along with the other model parameters and it makes way for strong statistical tools for inference studies.