{"title":"CryptKeeper: a negative design tool for reducing unintentional gene expression in bacteria","authors":"Cameron T. Roots, Jeffrey E. Barrick","doi":"10.1101/2024.09.05.611466","DOIUrl":null,"url":null,"abstract":"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 bacterial gene expression signals and estimates the translational burden possible from a DNA sequence. We investigate several published examples where cryptic gene expression in <em>E. coli</em> 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.","PeriodicalId":501408,"journal":{"name":"bioRxiv - Synthetic Biology","volume":"45 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"bioRxiv - Synthetic Biology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.09.05.611466","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0
Abstract
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 bacterial gene expression signals and estimates the translational burden possible from a DNA sequence. We investigate several published examples where cryptic gene expression in E. coli 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--依赖于将非本地或合成 DNA 序列引入生物体。这些序列在新的环境中可能会以非预期的方式被转录和翻译机器识别。事实证明,有时导致的隐性基因表达会产生遗传不稳定性并掩盖实验信号。目前已开发出一些计算工具来预测单个类型的基因表达元素,但研究人员很难将这些工具的集体输出结果与上下文联系起来。在这里,我们将介绍 CryptKeeper,它是一种可视化细菌基因表达信号预测并估算 DNA 序列可能产生的翻译负担的软件管道。我们研究了几个已发表的例子,其中大肠杆菌中的隐性基因表达干扰了实验。CryptKeeper 能准确预测真核病毒感染克隆和导致基因不稳定的单个蛋白质中不需要的基因表达。CryptKeeper 还能识别导致蛋白质纯化受阻的截断基因表达元件。在反向遗传学和合成生物学工作流程中使用 CryptKeeper 进行负设计,有助于减轻克隆挑战,避免因无意的基因表达而导致无法解释的失败和并发症。