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Achieving a Predictive Understanding of Antimicrobial Stress Physiology through Systems Biology.
Mack, Sean G; Turner, Randi L; Dwyer, Daniel J.
Afiliación
  • Mack SG; Department of Chemical & Biomolecular Engineering, University of Maryland, College Park, MD 20742, USA.
  • Turner RL; Department of Cell Biology & Molecular Genetics, University of Maryland, College Park, MD 20742, USA.
  • Dwyer DJ; Department of Chemical & Biomolecular Engineering, University of Maryland, College Park, MD 20742, USA; Department of Cell Biology & Molecular Genetics, University of Maryland, College Park, MD 20742, USA; Institute for Physical Sciences & Technology, University of Maryland, College Park, MD 20742, USA; Department of Bioengineering, University of Maryland, College Park, MD 20742, USA; Maryland Pathogen Research Institute, University of Maryland, College Park, MD 20742, USA. Electroni
Trends Microbiol ; 26(4): 296-312, 2018 04.
Article en En | MEDLINE | ID: mdl-29530606
ABSTRACT
The dramatic spread and diversity of antibiotic-resistant pathogens has significantly reduced the efficacy of essentially all antibiotic classes, bringing us ever closer to a postantibiotic era. Exacerbating this issue, our understanding of the multiscale physiological impact of antimicrobial challenge on bacterial pathogens remains incomplete. Concerns over resistance and the need for new antibiotics have motivated the collection of omics measurements to provide systems-level insights into antimicrobial stress responses for nearly 20 years. Although technological advances have markedly improved the types and resolution of such measurements, continued development of mathematical frameworks aimed at providing a predictive understanding of complex antimicrobial-associated phenotypes is critical to maximize the utility of multiscale data. Here we highlight recent efforts utilizing systems biology to enhance our knowledge of antimicrobial stress physiology. We provide a brief historical perspective of antibiotic-focused omics measurements, highlight new measurement discoveries and trends, discuss examples and opportunities for integrating measurements with mathematical models, and describe future challenges for the field.
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Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Estrés Fisiológico / Biología de Sistemas / Antiinfecciosos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Año: 2018 Tipo del documento: Article

Texto completo: 1 Banco de datos: MEDLINE Asunto principal: Estrés Fisiológico / Biología de Sistemas / Antiinfecciosos Tipo de estudio: Prognostic_studies / Risk_factors_studies Idioma: En Año: 2018 Tipo del documento: Article