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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...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2021
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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. |
format | Online Article Text |
id | pubmed-8688151 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
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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