ArticleNPJ systems biology and applications2021
Quantitative prediction of conditional vulnerabilities in regulatory and metabolic networks using PRIME.
Article in NPJ systems biology and applications, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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Who cites it
5 citing papers in PubMed.
- Article
- Mathematical models to study the biology of pathogens and the infectious diseases they cause.iScience · 2022Review
- MadR mediates acyl CoA-dependent regulation of mycolic acid desaturation in mycobacteria.Proceedings of the National Academy of Sciences of the United States of America · 2022Article
- Transcriptome signature of cell viability predicts drug response and drug interaction inCell reports methods · 2021Article
- Predictive regulatory and metabolic network models for systems analysis of Clostridioides difficile.Cell host & microbe · 2021Article
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Authors and funding
7 authors.
Funding
Abstract
The ability of Mycobacterium tuberculosis (Mtb) to adopt heterogeneous physiological states underlies its success in evading the immune system and tolerating antibiotic killing. Drug tolerant phenotypes are a major reason why the tuberculosis (TB) mortality rate is so high, with over 1.8 million deaths annually. To develop new TB therapeutics that better treat the infection (faster and more completely), a systems-level approach is needed to reveal the complexity of network-based adaptations of Mtb. Here, we report a new predictive model called PRIME (Phenotype of Regulatory influences Integrated with Metabolism and Environment) to uncover environment-specific vulnerabilities within the regulatory and metabolic networks of Mtb. Through extensive performance evaluations using genome-wide fitness screens, we demonstrate that PRIME makes mechanistically accurate predictions of context-specific vulnerabilities within the integrated regulatory and metabolic networks of Mtb, accurately rank-ordering targets for potentiating treatment with frontline drugs.
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