Journal
PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA
Volume 109, Issue 30, Pages 12254-12259Publisher
NATL ACAD SCIENCES
DOI: 10.1073/pnas.1201281109
Keywords
pairwise; entropy; prokaryotes; dose-response relationship
Categories
Funding
- National Institutes of Health (NIH) [P50GM081892-02]
- AFOSR [FA9550-11-1-0247]
- NIH through Rutgers University [1R01GM086881]
- National Science Foundation [0805462]
- Direct For Biological Sciences
- Div Of Biological Infrastructure [0805462] Funding Source: National Science Foundation
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Drugs are commonly used in combinations larger than two for treating bacterial infection. However, it is generally impossible to infer directly from the effects of individual drugs the net effect of a multidrug combination. Here we develop a mechanism-independent method for predicting the microbial growth response to combinations of more than two drugs. Performing experiments in both Gram-negative (Escherichia coli) and Gram-positive (Staphylococcus aureus) bacteria, we demonstrate that for a wide range of drugs, the bacterial responses to drug pairs are sufficient to infer the effects of larger drug combinations. To experimentally establish the broad applicability of the method, we use drug combinations comprising protein synthesis inhibitors (macrolides, aminoglycosides, tetracyclines, lincosamides, and chloramphenicol), DNA synthesis inhibitors (fluoroquinolones and quinolones), folic acid synthesis inhibitors (sulfonamides and diaminopyrimidines), cell wall synthesis inhibitors, polypeptide antibiotics, preservatives, and analgesics. Moreover, we show that the microbial responses to these drug combinations can be predicted using a simple formula that should be widely applicable in pharmacology. These findings offer a powerful, readily accessible method for the rational design of candidate therapies using combinations of more than two drugs. In addition, the accurate predictions of this framework raise the question of whether the multidrug response in bacteria obeys statistical, rather than chemical, laws for combinations larger than two.
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