Deciphering the Ecology of Cystic Fibrosis Bacterial Communities: Towards Systems-Level Integration
Jazyk angličtina Země Anglie, Velká Británie Médium print-electronic
Typ dokumentu časopisecké články, Research Support, N.I.H., Extramural, práce podpořená grantem, přehledy
Grantová podpora
K24 HL141669
NHLBI NIH HHS - United States
PubMed
31439509
DOI
10.1016/j.molmed.2019.07.008
PII: S1471-4914(19)30185-6
Knihovny.cz E-zdroje
- Klíčová slova
- cystic fibrosis, longitudinal studies, microbiome, microbiome-based therapy, predictive modeling, systems biology,
- MeSH
- Bacteria izolace a purifikace metabolismus MeSH
- cystická fibróza mikrobiologie terapie MeSH
- lidé MeSH
- mikrobiota MeSH
- plíce mikrobiologie MeSH
- systémová biologie metody MeSH
- zvířata MeSH
- Check Tag
- lidé MeSH
- zvířata MeSH
- Publikační typ
- časopisecké články MeSH
- práce podpořená grantem MeSH
- přehledy MeSH
- Research Support, N.I.H., Extramural MeSH
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.
Department of Biology University of Florence Sesto Fiorentino Florence Italy
Department of Pediatrics University of Washington Seattle WA USA
Citace poskytuje Crossref.org