Lying in Wait: Modeling the Control of Bacterial Infections via Antibiotic-Induced Proviruses

Author:

Clifton Sara M.1ORCID,Kim Ted2,Chandrashekhar Jayadevi H.2,O’Toole George A.3,Rapti Zoi14,Whitaker Rachel J.24

Affiliation:

1. Department of Mathematics, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

2. Department of Microbiology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

3. Department of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire, USA

4. Carl R. Woese Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois, USA

Abstract

Antibiotic resistance is a growing concern for management of common bacterial infections. Here, we show that antibiotics can be effective at subinhibitory levels when bacteria carry latent phage. Our findings suggest that specific treatment strategies based on the identification of latent viruses in individual bacterial strains may be an effective personalized medicine approach to antibiotic stewardship.

Funder

Allen Distinguished Investigator Award

HHS | National Institutes of Health

National Science Foundation

Cystic Fibrosis Foundation

Publisher

American Society for Microbiology

Subject

Computer Science Applications,Genetics,Molecular Biology,Modeling and Simulation,Ecology, Evolution, Behavior and Systematics,Biochemistry,Physiology,Microbiology

Reference110 articles.

1. The antibiotic resistance crisis: part 1: causes and threats;Ventola CL;P T,2015

2. Predominant pathogens in hospital infections

3. Antibiotic resistance in Pseudomonas aeruginosa: mechanisms and impact on treatment

4. Centers for Disease Control and Prevention. 2013. Antibiotic resistance threats in the United States, 2013. Centers for Disease Control and Prevention, Atlanta, GA.

5. The Epidemiology, Pathogenesis and Treatment of Pseudomonas aeruginosa Infections

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