Department of Integrative Biology, The University of Texas at Austin, Austin, TX, United States of America.
PLoS One. 2022 May 26;17(5):e0268883. doi: 10.1371/journal.pone.0268883. eCollection 2022.
Synthetic biology has successfully advanced our ability to design and implement complex, time-varying genetic circuits to control the expression of recombinant proteins. However, these circuits typically require the production of regulatory genes whose only purpose is to coordinate expression of other genes. When designing very small genetic constructs, such as viral genomes, we may want to avoid introducing such auxiliary gene products while nevertheless encoding complex expression dynamics. To this end, here we demonstrate that varying only the placement and strengths of promoters, terminators, and RNase cleavage sites in a computational model of a bacteriophage genome is sufficient to achieve solutions to a variety of basic gene expression patterns. We discover these genetic solutions by computationally evolving genomes to reproduce desired gene expression time-course data. Our approach shows that non-trivial patterns can be evolved, including patterns where the relative ordering of genes by abundance changes over time. We find that some patterns are easier to evolve than others, and comparable expression patterns can be achieved via different genetic architectures. Our work opens up a novel avenue to genome engineering via fine-tuning the balance of gene expression and gene degradation rates.
合成生物学成功地提高了我们设计和实现复杂、时变遗传电路以控制重组蛋白表达的能力。然而，这些电路通常需要产生调节基因，这些基因的唯一目的是协调其他基因的表达。在设计非常小的遗传构建体（如病毒基因组）时，我们可能希望避免引入此类辅助基因产物，同时仍然编码复杂的表达动力学。为此，我们在这里展示，仅通过改变计算模型中的噬菌体基因组中启动子、终止子和核糖核酸酶切割位点的位置和强度，就足以实现各种基本基因表达模式的解决方案。我们通过计算进化基因组来复制所需的基因表达时程数据来发现这些遗传解决方案。我们的方法表明，可以进化出非平凡的模式，包括基因丰度随时间变化的相对顺序发生变化的模式。我们发现，有些模式比其他模式更容易进化，并且可以通过不同的遗传结构来实现可比的表达模式。我们的工作通过微调基因表达和基因降解率之间的平衡，为基因组工程开辟了一条新途径。
