Roots Cameron T, Barrick Jeffrey E
Department of Molecular Biosciences, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, TX 78712, USA.
Synth Biol (Oxf). 2024 Dec 2;9(1):ysae018. doi: 10.1093/synbio/ysae018. eCollection 2024.
Foundational techniques in molecular biology-such as cloning genes, tagging biomolecules for purification or identification, and overexpressing recombinant proteins-rely on introducing non-native or synthetic DNA sequences into organisms. These sequences may be recognized by the transcription and translation machinery in their new context in unintended ways. The cryptic gene expression that sometimes results has been shown to produce genetic instability and mask experimental signals. Computational tools have been developed to predict individual types of gene expression elements, but it can be difficult for researchers to contextualize their collective output. Here, we introduce CryptKeeper, a software pipeline that visualizes predictions of gene expression signals and estimates the translational burden possible from a DNA sequence. We investigate several published examples where cryptic gene expression in interfered with experiments. CryptKeeper accurately postdicts unwanted gene expression from both eukaryotic virus infectious clones and individual proteins that led to genetic instability. It also identifies off-target gene expression elements that resulted in truncations that confounded protein purification. Incorporating negative design using CryptKeeper into reverse genetics and synthetic biology workflows can help to mitigate cloning challenges and avoid unexplained failures and complications that arise from unintentional gene expression.
分子生物学中的基础技术，如克隆基因、标记生物分子以进行纯化或鉴定，以及过表达重组蛋白，都依赖于将非天然或合成的DNA序列引入生物体。这些序列在新的环境中可能会被转录和翻译机制以意想不到的方式识别。有时产生的隐秘基因表达已被证明会导致遗传不稳定并掩盖实验信号。已经开发出计算工具来预测单个类型的基因表达元件，但研究人员很难将它们的总体输出置于具体情境中。在这里，我们介绍了CryptKeeper，这是一种软件流程，它可以可视化基因表达信号的预测，并估计DNA序列可能产生的翻译负担。我们研究了几个已发表的隐秘基因表达干扰实验的例子。CryptKeeper能够准确地事后预测真核病毒感染性克隆和导致遗传不稳定的单个蛋白质中不需要的基因表达。它还能识别导致截短从而混淆蛋白质纯化的脱靶基因表达元件。将使用CryptKeeper的负向设计纳入反向遗传学和合成生物学工作流程中，有助于减轻克隆挑战，避免因意外基因表达而产生的无法解释的失败和并发症。
