6 research outputs found
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 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 molecule
Massively parallel combinatorial microbiology
Thesis: Ph. D., Massachusetts Institute of Technology, Department of Biological Engineering, May, 2020Cataloged from PDF version of thesis.Includes bibliographical references (pages 203-216).Reductionist biology of the 20th century rooted pure culture methods and antibiotics as pillars of humankind's interaction with microbiology, igniting a revolution in medicine and biotechnology. The revolution was not without cost. By overlooking complex biological interactions, it introduced new problems--from the sharp rise in immune disorders to the antibiotic resistance crisis--that 21st century tools must address. While 'omics methods have fundamentally expanded our understanding of biological complexity, we lack a generalized method for measuring how the parts of a complex system, such as the individual strains of a microbial community, interact with each other. In this thesis, I present kChip, a new platform for constructing massively parallel combinatorial arrays of these parts in order to measure their interactions directly. I describe how kChip has been used to reveal patterns in microbial community assembly, unearth minimal microbial combinations with desirable functions, and screen for compounds that potentiate antibiotic activity. I demonstrate how kChip can advance the development of new technologies like microbial consortia and combinatorial drug therapies.by Jared Scott Kehe.Ph. D.Ph.D. Massachusetts Institute of Technology, Department of Biological Engineerin
Massively parallel screening of synthetic microbial communities
Microbial communities have numerous potential applications in biotechnology, agriculture, and medicine. Nevertheless, the limited accuracy with which we can predict interspecies interactions and environmental dependencies hinders efforts to rationally engineer beneficial consortia. Empirical screening is a complementary approach wherein synthetic communities are combinatorially constructed and assayed in high throughput. However, assembling many combinations of microbes is logistically complex and difficult to achieve on a timescale commensurate with microbial growth. Here, we introduce the kChip, a droplets-based platform that performs rapid, massively parallel, bottom-up construction and screening of synthetic microbial communities. We first show that the kChip enables phenotypic characterization of microbes across environmental conditions. Next, in a screen of ∼100,000 multispecies communities comprising up to 19 soil isolates, we identified sets that promote the growth of the model plant symbiont Herbaspirillum frisingense in a manner robust to carbon source variation and the presence of additional species. Broadly, kChip screening can identify multispecies consortia possessing any optically assayable function, including facilitation of biocontrol agents, suppression of pathogens, degradation of recalcitrant substrates, and robustness of these functions to perturbation, with many applications across basic and applied microbial ecology.National Science Foundation (U.S.). Graduate Research Fellowship (Fellow ID 2016220942)National Science Foundation (U.S.). Graduate Research Fellowship (Fellow ID 2013164251)Burroughs Wellcome Fund (Career Award at the Scientific Interface Grant 1010240)Simons Foundation (Grant 542385
Positive interactions are common among culturable bacteria
Positive interactions between bacteria, often described to be rare, occur commonly and primarily as parasitisms.</jats:p
Massively multiplexed nucleic acid detection using Cas13
The overwhelming majority of globally circulating pathogens go undetected, undermining patient care and hindering outbreak preparedness and response. To enable routine surveillance and comprehensive diagnostic applications, there is a need for detection technologies that can scale to test many samples while simultaneously testing for many pathogens. Here, we develop Combinatorial Arrayed Reactions for Multiplexed Evaluation of Nucleic acids (CARMEN), a platform for scalable, multiplexed pathogen detection. In the CARMEN platform, nanoliter droplets containing CRISPR-based nucleic acid detection reagents self-organize in a microwell array to pair with droplets of amplified samples, testing each sample against each CRISPR RNA (crRNA) in replicate. The combination of CARMEN and Cas13 detection (CARMEN-Cas13) enables robust testing of >4,500 crRNA-target pairs on a single array. Using CARMEN-Cas13, we developed a multiplexed assay that simultaneously differentiates all 169 human-associated viruses with ≥10 published genome sequences and rapidly incorporated an additional crRNA to detect the causative agent of the 2020 COVID-19 pandemic. CARMEN-Cas13 further enables comprehensive subtyping of influenza A strains and multiplexed identification of dozens of HIV drug-resistance mutations. CARMEN’s intrinsic multiplexing and throughput capabilities make it practical to scale, as miniaturization decreases reagent cost per test >300-fold. Scalable, highly-multiplexed CRISPR-based nucleic acid detection shifts diagnostic and surveillance efforts from targeted testing of high-priority samples to comprehensive testing of large sample sets, greatly benefiting patients and public health. ©202