Deciphering the Ecology of Cystic Fibrosis Bacterial Communities: Towards Systems-Level Integration

Download PDF [2 MB] Figures Save Share Reprints Request Top Deciphering the Ecology of Cystic Fibrosis Bacterial Communities: Towards Systems-Level Integration Annamaria Bevivino @ Giovanni Bacci Pavel Drevinek Maria T. Nelson Lucas Hoffman Alessio Mengoni Show footnotes Open AccessPublished:August 19, 2019DOI:https://doi.org/10.1016/j.molmed.2019.07.008 PlumX Metrics Highlights Keywords The CF Microbiota: Where Are We Now? Factors Influencing the Evaluation of CF Microbiota Many Singers, but Which Song(s)? Predicting CF Patient Respiratory Microbiome Interactions The Microbiome as a Therapeutic Target Concluding Remarks Acknowledgments References Glossary Article Info Figures Tables Related Articles Comments Marketplace Recommendations Influenza Virus Research Reagents World's largest influenza research tool bank covering 60+ subtypes & 250+ strains. – Sino Biological Mosquito-Borne Diseases: Research Tools Great range of tools for chikungunya, yellow fever, dengue and Zika research. – Biorbyt Why Use Lentivirus to Deliver DNA? Lentiviral vectors as gene delivery tool are modified from HIV-1, learn more – Origene Blood Lymphocyte Culture Special media optimized for the short-term culture of peripheral blood lymphocytes, order now Ads Powered with Highlights The analysis of CF respiratory microbiome data is rapidly increasing our understanding of the microbiological correlates of lung disease, fueling hope for rational design of therapeutics that target the microbiota or its behavior to improve the health of the CF lung. Recent work using metagenomic techniques has not only identified variable taxonomic composition of microbiota, but also a conserved set of functional microbial genes in patients with similar disease severity, suggesting functional redundancy that may present opportunities for treatments. These findings have led to harnessing the sputum microbiome composition as predictive over disease progression. Among the members of the microbiota, agonistic and antagonistic interactions have been disclosed, allowing the hypothesis of interventions based on the restoration of healthy ecological relationships inside the CF microbiome. Despite over a decade of cystic fibrosis (CF) microbiome research, much remains to be learned about the overall composition, metabolic activities, and pathogenicity of the microbes in CF airways, limiting our understanding of the respiratory microbiome’s relation to disease. Systems-level integration and modeling of host–microbiome interactions may allow us to better define the relationships between microbiological characteristics, disease status, and treatment response. In this way, modeling could pave the way for microbiome-based development of predictive models, individualized treatment plans, and novel therapeutic approaches, potentially serving as a paradigm for approaching other chronic infections. In this review, we describe the challenges facing this effort and propose research priorities for a systems biology approach to CF lung disease.