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Transcriptome signature of cell viability predicts drug response and drug interaction in Mycobacterium tuberculosis

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 transc...

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Detalles Bibliográficos
Autores principales: Srinivas, Vivek, Ruiz, Rene A., Pan, Min, Immanuel, Selva Rupa Christinal, Peterson, Eliza J.R., Baliga, Nitin S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8688151/
https://www.ncbi.nlm.nih.gov/pubmed/34977849
http://dx.doi.org/10.1016/j.crmeth.2021.100123
Descripción
Sumario: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.