Quantitative prediction of conditional vulnerabilities in regulatory and metabolic networks using PRIME.
Quantitative prediction of conditional vulnerabilities in regulatory and metabolic networks using PRIME.
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DOI：
10.1038/s41540-021-00205-6
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发表时间：
2021-12-06
影响因子：
4
通讯作者：
Baliga NS
中科院分区：
文献类型：
--
作者：
Immanuel SRC;Arrieta-Ortiz ML;Ruiz RA;Pan M;Lopez Garcia de Lomana A;Peterson EJR;Baliga NS
结核分枝杆菌（Mtb）采用异质生理状态的能力是其成功逃避免疫系统和耐受抗生素杀伤的基础。耐药表型是结核病（TB）死亡率如此之高的主要原因，每年有超过180万人死亡。为了开发更好地治疗感染（更快，更全面）的新结核病疗法，需要一种系统级方法来揭示结核病基于网络的适应性的复杂性。在这里，我们报告了一种新的预测模型，称为PRIME（与代谢和环境相结合的监管影响表型），以揭示结核分枝杆菌的监管和代谢网络中的环境特异性漏洞。通过使用全基因组适应性筛选进行广泛的性能评估，我们证明了PRIME在Mtb的综合监管和代谢网络中对特定环境的脆弱性进行了机械准确的预测，准确地排序了一线药物增强治疗的目标。
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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影响因子：
9.9
作者：
Arrieta-Ortiz ML;Hafemeister C;Bate AR;Chu T;Greenfield A;Shuster B;Barry SN;Gallitto M;Liu B;Kacmarczyk T;Santoriello F;Chen J;Rodrigues CD;Sato T;Rudner DZ;Driks A;Bonneau R;Eichenberger P
通讯作者：
Eichenberger P
影响因子：
48
作者：
Langmead, Ben;Salzberg, Steven L.
通讯作者：
Salzberg, Steven L.
影响因子：
5.8
作者：
Kim, Minsuk;Sun, Gwanggyu;Kim, Byung-Gee
通讯作者：
Kim, Byung-Gee
影响因子：
5.2
作者：
de Steenwinkel, Jurriaan E. M.;de Knegt, Gerjo J.;Bakker-Woudenberg, Irma A. J. M.
通讯作者：
Bakker-Woudenberg, Irma A. J. M.
结核分枝杆菌中基因调节和代谢网络的综合建模。
影响因子：
4.3
作者：
Ma S;Minch KJ;Rustad TR;Hobbs S;Zhou SL;Sherman DR;Price ND
通讯作者：
Price ND