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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
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author Srinivas, Vivek
Ruiz, Rene A.
Pan, Min
Immanuel, Selva Rupa Christinal
Peterson, Eliza J.R.
Baliga, Nitin S.
author_facet Srinivas, Vivek
Ruiz, Rene A.
Pan, Min
Immanuel, Selva Rupa Christinal
Peterson, Eliza J.R.
Baliga, Nitin S.
author_sort Srinivas, Vivek
collection PubMed
description 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.
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spelling pubmed-86881512021-12-30 Transcriptome signature of cell viability predicts drug response and drug interaction in Mycobacterium tuberculosis Srinivas, Vivek Ruiz, Rene A. Pan, Min Immanuel, Selva Rupa Christinal Peterson, Eliza J.R. Baliga, Nitin S. Cell Rep Methods Article 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. Elsevier 2021-12-06 /pmc/articles/PMC8688151/ /pubmed/34977849 http://dx.doi.org/10.1016/j.crmeth.2021.100123 Text en © 2021 The Authors https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Srinivas, Vivek
Ruiz, Rene A.
Pan, Min
Immanuel, Selva Rupa Christinal
Peterson, Eliza J.R.
Baliga, Nitin S.
Transcriptome signature of cell viability predicts drug response and drug interaction in Mycobacterium tuberculosis
title Transcriptome signature of cell viability predicts drug response and drug interaction in Mycobacterium tuberculosis
title_full Transcriptome signature of cell viability predicts drug response and drug interaction in Mycobacterium tuberculosis
title_fullStr Transcriptome signature of cell viability predicts drug response and drug interaction in Mycobacterium tuberculosis
title_full_unstemmed Transcriptome signature of cell viability predicts drug response and drug interaction in Mycobacterium tuberculosis
title_short Transcriptome signature of cell viability predicts drug response and drug interaction in Mycobacterium tuberculosis
title_sort transcriptome signature of cell viability predicts drug response and drug interaction in mycobacterium tuberculosis
topic Article
url 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
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