Dynamic Gene Expression Mitigates Mutational Escape in Lysis-Driven Bacteria Cancer Therapy

动态基因表达减轻裂解驱动细菌癌症治疗中的突变逃逸

阅读:11
作者:Filippo Liguori, Nicola Pellicciotta, Edoardo Milanetti, Sophia Xi Windemuth, Giancarlo Ruocco, Roberto Di Leonardo, Tal Danino

Abstract

Engineered bacteria have the potential to deliver therapeutic payloads directly to tumors, with synthetic biology enabling precise control over therapeutic release in space and time. However, it remains unclear how to optimize therapeutic bacteria for durable colonization and sustained payload release. Here, we characterize nonpathogenic Escherichia coli expressing the bacterial toxin Perfringolysin O (PFO) and dynamic strategies that optimize therapeutic efficacy. While PFO is known for its potent cancer cell cytotoxicity, we present experimental evidence that expression of PFO causes lysis of bacteria in both batch culture and microfluidic systems, facilitating its efficient release. However, prolonged expression of PFO leads to the emergence of a mutant population that limits therapeutic-releasing bacteria in a PFO expression level-dependent manner. We present sequencing data revealing the mutant takeover and employ molecular dynamics to confirm that the observed mutations inhibit the lysis efficiency of PFO. To analyze this further, we developed a mathematical model describing the evolution of therapeutic-releasing and mutant bacteria populations revealing trade-offs between therapeutic load delivered and fraction of mutants that arise. We demonstrate that a dynamic strategy employing short and repeated inductions of the pfo gene better preserves the original population of therapeutic bacteria by mitigating the effects of mutational escape. Altogether, we demonstrate how dynamic modulation of gene expression can address mutant takeovers giving rise to limitations in engineered bacteria for therapeutic applications.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。