利用高通量声学筛选实现声学报告基因的定向进化。

IF 3.7 2区 生物学 Q1 BIOCHEMICAL RESEARCH METHODS
Robert C. Hurt, Zhiyang Jin, Mohamed Soufi, Katie K. Wong, Daniel P. Sawyer, Hao K. Shen, Przemysław Dutka, Ramya Deshpande, Ruby Zhang, David R. Mittelstein and Mikhail G. Shapiro*, 
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引用次数: 0

摘要

生物成像和合成生物学领域面临的一大挑战是如何以非侵入方式观察不透明样本(如活体动物)内天然细胞和工程细胞的功能。超声波(US)穿透深度达数厘米,空间分辨率约为 100 微米,是解决这一局限性的一项前景广阔的技术。过去十年间,人们引入并设计了超声报告基因,通过在共生细菌和哺乳动物细胞中异源表达,将细胞功能与超声信号联系起来。这些声学报告基因(ARGs)代表了一类新型的基因编码 US 对比剂,其基础是被称为气泡(GVs)的充满空气的蛋白质纳米结构。正如荧光蛋白被发现后,其光学特性通过定向进化得到了改进和多样化一样,我们在此描述了作为声学报告因子的 GVs 的进化过程。为了完成这项任务,我们在细菌培养物中对 ARGs 进行了高通量、半自动声学筛选,并利用它筛选出具有更强非线性 US 散射的变体库。从主要 GV 结构蛋白 GvpA/B 的两个同源物的扫描位点饱和文库开始,经过两轮进化,GV 变体的声学信号分别比母体蛋白强 5 倍和 14 倍。我们预计,这种方法和类似方法将有助于高通量蛋白质工程在声学生物分子的开发中发挥与荧光生物分子相同的作用。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

Directed Evolution of Acoustic Reporter Genes Using High-Throughput Acoustic Screening

Directed Evolution of Acoustic Reporter Genes Using High-Throughput Acoustic Screening

Directed Evolution of Acoustic Reporter Genes Using High-Throughput Acoustic Screening

A major challenge in the fields of biological imaging and synthetic biology is noninvasively visualizing the functions of natural and engineered cells inside opaque samples such as living animals. One promising technology that addresses this limitation is ultrasound (US), with its penetration depth of several cm and spatial resolution on the order of 100 μm. Within the past decade, reporter genes for US have been introduced and engineered to link cellular functions to US signals via heterologous expression in commensal bacteria and mammalian cells. These acoustic reporter genes (ARGs) represent a novel class of genetically encoded US contrast agent, and are based on air-filled protein nanostructures called gas vesicles (GVs). Just as the discovery of fluorescent proteins was followed by the improvement and diversification of their optical properties through directed evolution, here we describe the evolution of GVs as acoustic reporters. To accomplish this task, we establish high-throughput, semiautomated acoustic screening of ARGs in bacterial cultures and use it to screen mutant libraries for variants with increased nonlinear US scattering. Starting with scanning site saturation libraries for two homologues of the primary GV structural protein, GvpA/B, two rounds of evolution resulted in GV variants with 5- and 14-fold stronger acoustic signals than the parent proteins. We anticipate that this and similar approaches will help high-throughput protein engineering play as large a role in the development of acoustic biomolecules as it has for their fluorescent counterparts.

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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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