Classic reaction kinetics can explain complex patterns of antibiotic action

zur Wiesch, Pia Abel, Abel, Soeren, Gkotzis, Spyridon, Ocampo, Paolo, Engelstaedter, Jan, Hinkley, Trevor, Magnus, Carsten, Waldor, Matthew K., Udekwu, Klas and Cohen, Ted (2015) Classic reaction kinetics can explain complex patterns of antibiotic action. Science Translational Medicine, 7 287: . doi:10.1126/scitranslmed.aaa8760


Author zur Wiesch, Pia Abel
Abel, Soeren
Gkotzis, Spyridon
Ocampo, Paolo
Engelstaedter, Jan
Hinkley, Trevor
Magnus, Carsten
Waldor, Matthew K.
Udekwu, Klas
Cohen, Ted
Title Classic reaction kinetics can explain complex patterns of antibiotic action
Journal name Science Translational Medicine   Check publisher's open access policy
ISSN 1946-6234
1946-6242
Publication date 2015-05-13
Year available 2015
Sub-type Article (original research)
DOI 10.1126/scitranslmed.aaa8760
Open Access Status DOI
Volume 7
Issue 287
Total pages 11
Place of publication Washington, DC United States
Publisher American Association for the Advancement of Science
Collection year 2016
Language eng
Formatted 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 singlecell 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 (R2 = 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 postantibiotic 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.
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Biological Sciences Publications
 
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Created: Thu, 24 Sep 2015, 12:15:01 EST by Jan Engelstaedter on behalf of School of Biological Sciences