In Vivo Gene Expression Dynamics of Tumor-Targeted Bacteria.
In Vivo Gene Expression Dynamics of Tumor-Targeted Bacteria.
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DOI：
10.1021/sb3000639
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发表时间：
2012-10-19
影响因子：
4.7
通讯作者：
Bhatia, Sangeeta N.
中科院分区：
文献类型：
--
作者：
Danino, Tal;Lo, Justin;Prindle, Arthur;Hasty, Jeff;Bhatia, Sangeeta N.
对细菌进行工程改造以可控地递送治疗剂是合成生物学的一个有吸引力的应用。虽然大多数合成基因网络已经在微生物中进行了探索，但在积极研究宿主微生物的功效和安全性的应用背景下，如肿瘤药物递送，需要进一步表征体内回路行为。一个主要的障碍是，基于培养的选择性压力在体内是不存在的，导致基于质粒的网络随时间的应变依赖性不稳定性。在这里，我们实验特点的动态体内质粒不稳定性使用减毒菌株的S。鼠伤寒沙门氏菌和发光报告子的实时监测。计算建模描述了生长速率和剂量对内部细菌种群产生的实时成像信号的影响。这种理解将使我们能够利用基于质粒的网络的瞬时性质来创建可调的时间释放曲线，从而降低剂量需求并提高细菌治疗的安全性。
The engineering of bacteria to controllably deliver therapeutics is an attractive application for synthetic biology. While most synthetic gene networks have been explored within microbes, there is a need for further characterization of in vivo circuit behavior in the context of applications where the host microbes are actively being investigated for efficacy and safety, such as tumor drug delivery. One major hurdle is that culture-based selective pressures are absent in vivo, leading to strain-dependent instability of plasmid-based networks over time. Here, we experimentally characterize the dynamics of in vivo plasmid instability using attenuated strains of S. typhimurium and real-time monitoring of luminescent reporters. Computational modeling described the effects of growth rate and dosage on live-imaging signals generated by internal bacterial populations. This understanding will allow us to harness the transient nature of plasmid-based networks to create tunable temporal release profiles that reduce dosage requirements and increase the safety of bacterial therapies.
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影响因子：
46.9
作者：
Yu, YA;Shabahang, S;Szalay, AA
通讯作者：
Szalay, AA
影响因子：
5.5
作者：
Hohmann, EL;Oletta, CA;Miller, SI
通讯作者：
Miller, SI
影响因子：
5.1
作者：
Guo, H.;Zhang, J.;Inal, C.
通讯作者：
Inal, C.
影响因子：
64.8
作者：
通讯作者：
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影响因子：
45.3
作者：
Toso, JF;Gill, VJ;Rosenberg, SA
通讯作者：
Rosenberg, SA