Enhancing heterologous expression in Chlamydomonas reinhardtii by transcript sequence optimization

First author: Iddo Weiner; Affiliations: Tel Aviv University (特拉维夫大学): Tel Aviv, Israel

Corresponding author: Iftach Yacoby

Various species of microalgae (微藻) have recently emerged as promising host-organisms (宿主生物) for use in biotechnology industries due to their unique properties. These include efficient conversion of sunlight into organic compounds (有机化合物), the ability to grow in extreme conditions and the occurrence of numerous post-translational (翻译后) modification pathways. However, the inability to obtain high levels of nuclear heterologous (异源的) gene expression in microalgae hinders (阻碍) the development of the entire field. To overcome this limitation, we analyzed different sequence optimization algorithms while studying the effect of transcript sequence features on heterologous expression in the model microalga Chlamydomonas reinhardtii (莱茵藻), whose genome consists of rare features such as a high GC content. Based on the analysis of genomic data, we created eight unique sequences coding for a synthetic ferredoxin–hydrogenase enzyme (铁氧还蛋白氢化酶), used here as a reporter gene. Following in silico (生物信息学) design, these synthetic genes were transformed into the C. reinhardtii nucleus, after which gene expression levels were measured. The empirical data (实验数据), measured in vivo show a discrepancy (差异) of up to 65-fold between the different constructs. In this work we demonstrate how the combination of computational methods and our empirical results enable us to learn about the way gene expression is encoded in the C. reinhardtii transcripts. We describe the deleterious effect on overall expression of codons encoding for splicing signals. Subsequently, our analysis shows that utilization of a frequent subset of preferred codons results in elevated transcript levels, and that mRNA folding energy in the vicinity (附近) of translation initiation (翻译起始) significantly affects gene expression.

微藻中的大多数物种因为其独特的特性逐步成为生物技术工业的具有潜力的宿主生物。这些特性包括将光能有效转化为有机化合物、极端条件下生长的能力以及大量翻译后修饰通路的发生。然而，微藻中高水平核异源性基因表达难以获取，严重阻碍了整个领域的发展。为了克服这个限制，作者在研究模式微藻莱茵藻的转录序列性质对于其表达的影响时，分析了不同的序列最优法则。莱茵藻的基因组具有一些非常罕见的特性，比如其基因组GC含量十分之高。基于对基因组数据的分析，作者构建了8个独特的人工合成的铁氧还蛋白氢化酶，并用作报告基因。在生物信息学设计之后，作者将这些人工合成的基因转入到莱茵藻的核中，并在随后测量了这些基因的表达情况。体内基因表达的实验数据显示在不同的构建体中差异最大可达到65倍。本文中作者的研究结合计算生物学和分子试验揭示了在莱茵藻中转录本的基因表达是如何被编码的。作者还描述了对于编码剪切信号的密码子整体表达的有害影响。其后，本文的研究显示了通过最优密码子的利用可以提升转录水平，在翻译起始附近的mRNA折叠能量显著影响基因的表达。

通讯：Iftach Yacoby (https://en-lifesci.tau.ac.il/profile/iftachy)

研究方向：藻株的生物技术设计；人工合成酶的生物工程；能量传递瓶颈的研究。

doi: 10.1111/tpj.13836

Journal: the plant journal

Published date: 12 March, 2018

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