Combinatorial drug discovery in nanoliter droplets

Combinatorial drug treatment strategies perturb biological networks synergistically to achieve therapeutic effects and represent major opportunities to develop advanced treatments across a variety of human disease areas. However, the discovery of new combinatorial treatments is challenged by the she...

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Bibliographic Details
Main Authors: Kulesa, Anthony Benjamin, Kehe, Jared Scott, Hurtado, Juan E., Tawde, Prianca K., Blainey, Paul C
Other Authors: Massachusetts Institute of Technology. Department of Biological Engineering
Format: Article
Published: National Academy of Sciences (U.S.) 2019
Online Access:http://hdl.handle.net/1721.1/120291
https://orcid.org/0000-0001-9927-9715
https://orcid.org/0000-0002-1028-5981
https://orcid.org/0000-0001-7014-3830
Description
Summary:Combinatorial drug treatment strategies perturb biological networks synergistically to achieve therapeutic effects and represent major opportunities to develop advanced treatments across a variety of human disease areas. However, the discovery of new combinatorial treatments is challenged by the sheer scale of combinatorial chemical space. Here, we report a high-throughput system for nanoliter-scale phenotypic screening that formulates a chemical library in nanoliter droplet emulsions and automates the construction of chemical combinations en masse using parallel droplet processing. We applied this system to predict synergy between more than 4,000 investigational and approved drugs and a panel of 10 antibiotics against Escherichia coli, a model gram-negative pathogen. We found a range of drugs not previously indicated for infectious disease that synergize with antibiotics. Our validated hits include drugs that synergize with the antibiotics vancomycin, erythromycin, and novobiocin, which are used against gram-positive bacteria but are not effective by themselves to resolve gram-negative infections. Keywords: high-throughput screening; nanoliter droplet; drug synergy; antibiotics; small molecules