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Sci Transl Med. 2015 May 13;7(287):287ra73. doi: 10.1126/scitranslmed.aaa8760.

Classic reaction kinetics can explain complex patterns of antibiotic action.

Author information

1
Division of Global Health Equity, Brigham and Women's Hospital and Harvard Medical School, 641 Huntington Avenue, Boston, MA 02115, USA. Department of Epidemiology of Microbial Diseases, Yale School of Public Health, 60 College Street, New Haven, CT 06510, USA. pzw@daad-alumni.de.
2
Division of Infectious Diseases, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA 02115, USA. Department of Pharmacy, UiT, The Arctic University of Norway, 9037 Tromsø, Norway.
3
Department of Neuroscience, Karolinska Institutet, Retzius väg 8, 17177 Stockholm, Sweden.
4
Institute of Integrative Biology, ETH Zürich, Universitätsstrasse 16, 8092 Zürich, Switzerland. Department of Environmental Microbiology, EAWAG, Überlandstrasse 133, 8600 Dübendorf, Switzerland.
5
School of Biological Sciences, University of Queensland, Brisbane, Queensland 4072, Australia.
6
School of Chemistry, University of Glasgow, University Avenue, Glasgow G12 8QQ, UK.
7
Institute of Medical Virology, University of Zürich, Winterthurerstrasse 190, 8057 Zürich, Switzerland.
8
Division of Infectious Diseases, Brigham and Women's Hospital and Harvard Medical School, 181 Longwood Avenue, Boston, MA 02115, USA. Howard Hughes Medical Institute, 181 Longwood Avenue, Boston, MA 02115, USA.
9
Division of Global Health Equity, Brigham and Women's Hospital and Harvard Medical School, 641 Huntington Avenue, Boston, MA 02115, USA. Department of Epidemiology of Microbial Diseases, Yale School of Public Health, 60 College Street, New Haven, CT 06510, USA. Department of Epidemiology, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA.

Abstract

Finding optimal dosing strategies for treating bacterial infections is extremely difficult, and improving therapy requires costly and time-intensive experiments. To date, an incomplete mechanistic understanding of drug effects has limited our ability to make accurate quantitative predictions of drug-mediated bacterial killing and impeded the rational design of antibiotic treatment strategies. Three poorly understood phenomena complicate predictions of antibiotic activity: post-antibiotic growth suppression, density-dependent antibiotic effects, and persister cell formation. We show that chemical binding kinetics alone are sufficient to explain these three phenomena, using single-cell data and time-kill curves of Escherichia coli and Vibrio cholerae exposed to a variety of antibiotics in combination with a theoretical model that links chemical reaction kinetics to bacterial population biology. Our model reproduces existing observations, has a high predictive power across different experimental setups (R(2) = 0.86), and makes several testable predictions, which we verified in new experiments and by analyzing published data from a clinical trial on tuberculosis therapy. Although a variety of biological mechanisms have previously been invoked to explain post-antibiotic growth suppression, density-dependent antibiotic effects, and especially persister cell formation, our findings reveal that a simple model that considers only binding kinetics provides a parsimonious and unifying explanation for these three complex, phenotypically distinct behaviours. Current antibiotic and other chemotherapeutic regimens are often based on trial and error or expert opinion. Our "chemical reaction kinetics"-based approach may inform new strategies, which are based on rational design.

PMID:
25972005
PMCID:
PMC4554720
DOI:
10.1126/scitranslmed.aaa8760
[Indexed for MEDLINE]
Free PMC Article
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