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Journal Article

Cystic fibrosis therapy: A community ecology perspective

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http://pubman.mpdl.mpg.de/cone/persons/resource/persons56872

Rainey,  Paul B.
External Scientific Member Group Experimental and Evolutionary Genetics, Max Planck Institute for Evolutionary Biology, Max Planck Society;

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Conrad, D., Haynes, M., Salamon, P., Rainey, P. B., Youle, M., & Rohwer, F. (2013). Cystic fibrosis therapy: A community ecology perspective. American Journal of Respiratory Cell and Molecular Biology, 48(2), 150-156. doi:10.1165/rcmb.2012-0059PS.


Cite as: http://hdl.handle.net/11858/00-001M-0000-000E-E588-1
Abstract
Current therapy for cystic fibrosis (CF) focuses on minimizing the microbial community and the host’s immune response through the aggressive use of airway clearance techniques, broad-spectrum antibiotics, and treatments that break down the pervasive endobronchial biofilm.Antibiotic selection is typically based on the susceptibility of individual microbial strains to specific antibiotics in vitro. Often this approach cannot accurately predict medical outcomes because of factors both technical and biological. Recent cultureindependent assessments of the airway microbial and viral communities demonstrated that the CF airway infection is considerably more complex and dynamic than previously appreciated. Understanding the ecological and evolutionary pressures that shape these communities is critically important for the optimal use of current therapies (in both the choice of therapy and timing of administration) and the development of newer strategies. The climax–attack model (CAM) presented here, grounded in basic ecological principles, postulates the existence of two major functional communities. The attack community consists of transient viral and microbial populations that induce strong innate immune responses. The resultant intense immune response creates microenvironments that facilitate the establishment of a climax community that is slower-growing and inherently resistant to antibiotic therapy. Newermethodologies, including sequence-based metagenomic analysis, can track not only the taxonomic composition but also the metabolic capabilities of these changing viral andmicrobial communities over time. Collecting this informationforCFairwayswill enable themathematicalmodeling of microbial community dynamics during disease progression. The resultant understanding of airway communities and their effects on lung physiology will facilitate the optimization of CF therapies.