| Literature DB >> 31439509 |
Annamaria Bevivino1, Giovanni Bacci2, Pavel Drevinek3, Maria T Nelson4, Lucas Hoffman5, Alessio Mengoni2.
Abstract
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.Entities:
Keywords: cystic fibrosis; longitudinal studies; microbiome; microbiome-based therapy; predictive modeling; systems biology
Mesh:
Year: 2019 PMID: 31439509 DOI: 10.1016/j.molmed.2019.07.008
Source DB: PubMed Journal: Trends Mol Med ISSN: 1471-4914 Impact factor: 11.951