Modeling coding sequence design for virus-based expression in tobacco

IF 4.4 2区 生物学 Q1 BIOTECHNOLOGY & APPLIED MICROBIOLOGY Synthetic and Systems Biotechnology Pub Date : 2024-12-11 DOI:10.1016/j.synbio.2024.12.002
Moritz Burghardt , Tamir Tuller
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Abstract

Transient expression in Tobacco is a popular way to produce recombinant proteins in plants. The design of various expression vectors, delivered into the plant by Agrobacterium, has enabled high production levels of some proteins. To further enhance expression, researchers often adapt the coding sequence of heterologous genes to the host, but this strategy has produced mixed results in Tobacco.
To study the effects of different sequence features on protein yield, we compile a dataset of the yields and coding sequences of previously published expression studies of more than 200 coding sequences.
We evaluate various established gene expression models on a subset of the expression studies. We find that use of tobacco codons is only moderately predictive of protein yield as informative sequence features likely extend over multiple codons. Additionally, we show that codon usage of organisms that use tobacco as a host for expression of their proteins in a similar way as the synthetic system, like viruses and agrobacteria, can be used to predict heterologous expression. Other predictive features are related to tRNA supply and demand, the inclusion of a translational ramp of codons with lower adaptation to the tRNA pool at the beginning of the coding region, and the amino acid composition of the recombinant protein. A model based on all the features achieved a correlation of 0.57 with protein yield.
We believe that our study provides a practical guideline for coding sequence design for efficient expression in tobacco.
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为基于病毒的烟草表达设计编码序列模型。
烟草瞬时表达是一种在植物中产生重组蛋白的常用方法。设计各种表达载体,通过农杆菌传递到植物中,使一些蛋白质的高产量成为可能。为了进一步增强表达,研究人员经常将异源基因的编码序列适应宿主,但这种策略在烟草中产生了不同的结果。为了研究不同序列特征对蛋白产率的影响,我们编制了一个数据集,其中包含了200多个已发表的表达研究的编码序列的产率和编码序列。我们在表达研究的一个子集上评估各种已建立的基因表达模型。我们发现烟草密码子的使用只能适度预测蛋白质产量,因为信息序列特征可能延伸到多个密码子上。此外,我们还发现,以烟草为宿主表达其蛋白质的生物,如病毒和农杆菌,密码子的使用方式与合成系统类似,可用于预测异源表达。其他预测特征与tRNA的供需、编码区开头对tRNA库适应性较低的密码子翻译斜坡的包含以及重组蛋白的氨基酸组成有关。基于所有特征的模型与蛋白质产量的相关系数为0.57。我们相信我们的研究为烟草高效表达的编码序列设计提供了实用的指导。
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来源期刊
Synthetic and Systems Biotechnology
Synthetic and Systems Biotechnology BIOTECHNOLOGY & APPLIED MICROBIOLOGY-
CiteScore
6.90
自引率
12.50%
发文量
90
审稿时长
67 days
期刊介绍: Synthetic and Systems Biotechnology aims to promote the communication of original research in synthetic and systems biology, with strong emphasis on applications towards biotechnology. This journal is a quarterly peer-reviewed journal led by Editor-in-Chief Lixin Zhang. The journal publishes high-quality research; focusing on integrative approaches to enable the understanding and design of biological systems, and research to develop the application of systems and synthetic biology to natural systems. This journal will publish Articles, Short notes, Methods, Mini Reviews, Commentary and Conference reviews.
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