沉默之声:哺乳动物细胞工程中的转基因沉默。

IF 9 1区 生物学 Q1 BIOCHEMISTRY & MOLECULAR BIOLOGY
Alan Cabrera, Hailey I Edelstein, Fokion Glykofrydis, Kasey S Love, Sebastian Palacios, Josh Tycko, Meng Zhang, Sarah Lensch, Cara E Shields, Mark Livingston, Ron Weiss, Huimin Zhao, Karmella A Haynes, Leonardo Morsut, Yvonne Y Chen, Ahmad S Khalil, Wilson W Wong, James J Collins, Susan J Rosser, Karen Polizzi, Michael B Elowitz, Martin Fussenegger, Isaac B Hilton, Joshua N Leonard, Lacramioara Bintu, Kate E Galloway, Tara L Deans
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引用次数: 0

摘要

为了阐明天然生物系统的运作原理和开发新的生物技术,合成生物学的目标是在天然转录网络中构建和整合合成基因回路。合成基因电路在细胞工程中的应用依赖于控制所有转基因成分表达的能力。转基因沉默,定义为随着时间的推移表达的丧失,一直是用转基因货物改造原代细胞和干细胞的障碍。在这篇综述中,我们强调了转基因沉默给哺乳动物细胞的稳健工程带来的挑战,概述了沉默的潜在分子机制,并提出了预防转基因沉默的方法。最后展望了今后提高合成基因电路性能的研究方向。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The sound of silence: Transgene silencing in mammalian cell engineering.

To elucidate principles operating in native biological systems and to develop novel biotechnologies, synthetic biology aims to build and integrate synthetic gene circuits within native transcriptional networks. The utility of synthetic gene circuits for cell engineering relies on the ability to control the expression of all constituent transgene components. Transgene silencing, defined as the loss of expression over time, persists as an obstacle for engineering primary cells and stem cells with transgenic cargos. In this review, we highlight the challenge that transgene silencing poses to the robust engineering of mammalian cells, outline potential molecular mechanisms of silencing, and present approaches for preventing transgene silencing. We conclude with a perspective identifying future research directions for improving the performance of synthetic gene circuits.

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来源期刊
Cell Systems
Cell Systems Medicine-Pathology and Forensic Medicine
CiteScore
16.50
自引率
1.10%
发文量
84
审稿时长
42 days
期刊介绍: In 2015, Cell Systems was founded as a platform within Cell Press to showcase innovative research in systems biology. Our primary goal is to investigate complex biological phenomena that cannot be simply explained by basic mathematical principles. While the physical sciences have long successfully tackled such challenges, we have discovered that our most impactful publications often employ quantitative, inference-based methodologies borrowed from the fields of physics, engineering, mathematics, and computer science. We are committed to providing a home for elegant research that addresses fundamental questions in systems biology.
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