How can the cystic fibrosis respiratory microbiome influence our clinical decision-making?

Geraint B. Rogers*, Kenneth D. Bruce, Lucas R. Hoffman

*Corresponding author for this work

Research output: Contribution to journalReview articlepeer-review

13 Citations (Scopus)
178 Downloads (Pure)

Abstract

Purpose of review Almost 15 years have now passed since bacterial community profiling techniques were first used to analyse respiratory samples from people with cystic fibrosis. Since then, many different analytical approaches have been used to try to better understand the contribution of the cystic fibrosis lung microbiota to disease, with varying degrees of success. We examine the extent to which cystic fibrosis respiratory microbiome research has been successful in informing clinical decision-making, and highlight areas that we believe have the potential to yield important insight. Recent findings Recent research on the cystic fibrosis lung microbiome can be broadly divided into efforts to better characterize microbiota composition, particularly relative to key clinical events, and attempts to understand the cystic fibrosis lung microbiology as an interactive microbial system. The latter, in particular, has led to the development of a number of models in which microbiome-mediated processes precipitate clinical events. Summary Growing technological sophistication is enabling increasingly detailed microbiological data to be generated from cystic fibrosis respiratory samples. However, translating these data into clinically useful measures that accurately predict outcomes and guide treatments remains a formidable challenge. The development of systems biology approaches that enable the integration of complex microbiome and host-derived data provide an exciting opportunity to address this goal.

Original languageEnglish
Pages (from-to)536-543
Number of pages8
JournalCurrent Opinion in Pulmonary Medicine
Volume23
Issue number6
DOIs
Publication statusPublished - 1 Nov 2017

Keywords

  • microbial ecology
  • pulmonary exacerbations
  • systems biology

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