Revealing the dynamics of polymicrobial infections: implications for antibiotic therapy

Geraint B. Rogers; Lucas R. Hoffman; Marvin Whiteley; Thomas W. V. Daniels; Mary P. Carroll; Kenneth D. Bruce

doi:10.1016/j.tim.2010.04.005

Revealing the dynamics of polymicrobial infections: implications for antibiotic therapy

Geraint B. Rogers, Lucas R. Hoffman, Marvin Whiteley, Thomas W. V. Daniels, Mary P. Carroll, Kenneth D. Bruce

Institute of Pharmaceutical Science

Research output: Contribution to journal › Literature review › peer-review

56 Citations (Scopus)

Abstract

As a new generation of culture-independent analytical strategies emerge, the amount of data on polymicrobial infections will increase dramatically. For these data to inform clinical thinking, and in turn to maximise benefits for patients, an appropriate framework for their interpretation is required. Here, we use cystic fibrosis (CF) lower airway infections as a model system to examine how conceptual and technological advances can address two clinical questions that are central to improved management of CF respiratory disease. Firstly, can markers of the microbial community be identified that predict a change in infection dynamics and clinical outcomes? Secondly, can these new strategies directly characterize the impact of antimicrobial therapies, allowing treatment efficacy to be both assessed and optimized?

Original language	English
Pages (from-to)	357 - 364
Number of pages	8
Journal	Trends in Microbiology
Volume	18
Issue number	8
DOIs	https://doi.org/10.1016/j.tim.2010.04.005
Publication status	Published - Aug 2010

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

Access to Document

10.1016/j.tim.2010.04.005

Cite this

@article{0bb6e456c6064000ac93bff2a53d9ba3,

title = "Revealing the dynamics of polymicrobial infections: implications for antibiotic therapy",

abstract = "As a new generation of culture-independent analytical strategies emerge, the amount of data on polymicrobial infections will increase dramatically. For these data to inform clinical thinking, and in turn to maximise benefits for patients, an appropriate framework for their interpretation is required. Here, we use cystic fibrosis (CF) lower airway infections as a model system to examine how conceptual and technological advances can address two clinical questions that are central to improved management of CF respiratory disease. Firstly, can markers of the microbial community be identified that predict a change in infection dynamics and clinical outcomes? Secondly, can these new strategies directly characterize the impact of antimicrobial therapies, allowing treatment efficacy to be both assessed and optimized?",

author = "Rogers, {Geraint B.} and Hoffman, {Lucas R.} and Marvin Whiteley and Daniels, {Thomas W. V.} and Carroll, {Mary P.} and Bruce, {Kenneth D.}",

year = "2010",

month = aug,

doi = "10.1016/j.tim.2010.04.005",

language = "English",

volume = "18",

pages = "357 -- 364",

journal = "Trends in Microbiology",

publisher = "Elsevier Limited",

number = "8",

}

TY - JOUR

T1 - Revealing the dynamics of polymicrobial infections: implications for antibiotic therapy

AU - Rogers, Geraint B.

AU - Hoffman, Lucas R.

AU - Whiteley, Marvin

AU - Daniels, Thomas W. V.

AU - Carroll, Mary P.

AU - Bruce, Kenneth D.

PY - 2010/8

Y1 - 2010/8

N2 - As a new generation of culture-independent analytical strategies emerge, the amount of data on polymicrobial infections will increase dramatically. For these data to inform clinical thinking, and in turn to maximise benefits for patients, an appropriate framework for their interpretation is required. Here, we use cystic fibrosis (CF) lower airway infections as a model system to examine how conceptual and technological advances can address two clinical questions that are central to improved management of CF respiratory disease. Firstly, can markers of the microbial community be identified that predict a change in infection dynamics and clinical outcomes? Secondly, can these new strategies directly characterize the impact of antimicrobial therapies, allowing treatment efficacy to be both assessed and optimized?

AB - As a new generation of culture-independent analytical strategies emerge, the amount of data on polymicrobial infections will increase dramatically. For these data to inform clinical thinking, and in turn to maximise benefits for patients, an appropriate framework for their interpretation is required. Here, we use cystic fibrosis (CF) lower airway infections as a model system to examine how conceptual and technological advances can address two clinical questions that are central to improved management of CF respiratory disease. Firstly, can markers of the microbial community be identified that predict a change in infection dynamics and clinical outcomes? Secondly, can these new strategies directly characterize the impact of antimicrobial therapies, allowing treatment efficacy to be both assessed and optimized?

U2 - 10.1016/j.tim.2010.04.005

DO - 10.1016/j.tim.2010.04.005

M3 - Literature review

VL - 18

SP - 357

EP - 364

JO - Trends in Microbiology

JF - Trends in Microbiology

IS - 8

ER -

Revealing the dynamics of polymicrobial infections: implications for antibiotic therapy

Abstract

UN SDGs

Access to Document

Fingerprint

Cite this