Robust Inducible Gene Expression in Intracellular Listeria monocytogenes In Vivo.

IF 3.9 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
ACS Synthetic Biology Pub Date : 2025-05-16 Epub Date: 2025-04-25 DOI:10.1021/acssynbio.5c00131
Huong Giang Pham, Kiet N Tran, Larissa Gomelsky, Tathagato Roy, Jason P Gigley, Mark Gomelsky
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引用次数: 0

Abstract

Attenuated strains of the intracellular pathogen Listeria monocytogenes can deliver genetically encoded payloads inside tumor cells. L. monocytogenes preferentially accumulates and propagates in immune-suppressed tumor microenvironments. To maximize the payload impact in tumors and minimize damage to healthy tissues, it is desirable to induce payload synthesis when bacteria are eliminated from the healthy tissues but are grown to high numbers intratumorally. Here, we have engineered a tightly controlled gene expression system for intracellular L. monocytogenes inducible with a cumin derivative, cumate. Upon cumate addition, expression of a reporter gene is increased in L. monocytogenes growing in vitro by 80-fold and in intracellular L. monocytogenes in murine tumors by 75-fold. This study demonstrates the feasibility of activating gene expression in intracellular bacteria in live animals using an edible inducer. The system is expected to enhance the efficacy and safety of the attenuated L. monocytogenes strains as antitumor payload delivery bacterial drones.

单核增生李斯特菌胞内诱导基因在体内的强大表达。
细胞内病原体单核增生李斯特菌的减毒菌株可以在肿瘤细胞内传递遗传编码的有效载荷。单核细胞增生乳杆菌优先在免疫抑制的肿瘤微环境中积累和繁殖。为了最大限度地提高有效载荷对肿瘤的影响,并最大限度地减少对健康组织的损害,当细菌从健康组织中消除,但在瘤内生长到大量时,需要诱导有效载荷合成。在这里,我们设计了一个用孜然衍生物cumate诱导的细胞内单核细胞增生乳杆菌的严格控制的基因表达系统。在体外培养的单核细胞增生乳杆菌中,一个报告基因的表达增加了80倍,在小鼠肿瘤细胞内的单核细胞增生乳杆菌中,报告基因的表达增加了75倍。本研究证明了使用可食用诱导剂激活活动物胞内细菌基因表达的可行性。该系统有望提高单核增生乳杆菌减毒菌株作为抗肿瘤有效载荷递送细菌无人机的有效性和安全性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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来源期刊
CiteScore
8.00
自引率
10.60%
发文量
380
审稿时长
6-12 weeks
期刊介绍: The journal is particularly interested in studies on the design and synthesis of new genetic circuits and gene products; computational methods in the design of systems; and integrative applied approaches to understanding disease and metabolism. Topics may include, but are not limited to: Design and optimization of genetic systems Genetic circuit design and their principles for their organization into programs Computational methods to aid the design of genetic systems Experimental methods to quantify genetic parts, circuits, and metabolic fluxes Genetic parts libraries: their creation, analysis, and ontological representation Protein engineering including computational design Metabolic engineering and cellular manufacturing, including biomass conversion Natural product access, engineering, and production Creative and innovative applications of cellular programming Medical applications, tissue engineering, and the programming of therapeutic cells Minimal cell design and construction Genomics and genome replacement strategies Viral engineering Automated and robotic assembly platforms for synthetic biology DNA synthesis methodologies Metagenomics and synthetic metagenomic analysis Bioinformatics applied to gene discovery, chemoinformatics, and pathway construction Gene optimization Methods for genome-scale measurements of transcription and metabolomics Systems biology and methods to integrate multiple data sources in vitro and cell-free synthetic biology and molecular programming Nucleic acid engineering.
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