Title
Transcriptome signature of cell viability predicts drug response and drug interaction in
Document Type
Article
Publication Date
12-20-2021
Publication Title
Cell Rep Methods
Keywords
washington; seattle; isb
Abstract
There is an urgent need for new drug regimens to rapidly cure tuberculosis. Here, we report the development of drug response assayer (DRonA) and "MLSynergy," algorithms to perform rapid drug response assays and predict response of Mycobacterium tuberculosis (Mtb) to drug combinations. Using a transcriptome signature for cell viability, DRonA detects Mtb killing by diverse mechanisms in broth culture, macrophage infection, and patient sputum, providing an efficient and more sensitive alternative to time- and resource-intensive bacteriologic assays. Further, MLSynergy builds on DRonA to predict synergistic and antagonistic multidrug combinations using transcriptomes of Mtb treated with single drugs. Together, DRonA and MLSynergy represent a generalizable framework for rapid monitoring of drug effects in host-relevant contexts and accelerate the discovery of efficacious high-order drug combinations.
Department
Institute for Systems Biology
Department
Pharmacy
Recommended Citation
Srinivas, Vivek; Ruiz, Rene A; Pan, Min; Immanuel, Selva Rupa Christinal; Peterson, Eliza Jr; and Baliga, Nitin S, "Transcriptome signature of cell viability predicts drug response and drug interaction in" (2021). Articles, Abstracts, and Reports. 5744.
https://digitalcommons.providence.org/publications/5744