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Optimized genome-wide CRISPR screening enables rapid engineering of growth-based phenotypes in Yarrowia lipolytica
Metabolic Engineering ( IF 6.8 ) Pub Date : 2024-09-13 , DOI: 10.1016/j.ymben.2024.09.005
Nicholas R. Robertson, Varun Trivedi, Brian Lupish, Adithya Ramesh, Yuna Aguilar, Stephanie Carrera, Sangcheon Lee, Anthony Arteaga, Alexander Nguyen, Chase Lenert-Mondou, Marcus Harland-Dunaway, Robert Jinkerson, Ian Wheeldon

CRISPR-Cas9 functional genomic screens uncover gene targets linked to various phenotypes for metabolic engineering with remarkable efficiency. However, these genome-wide screens face a number of design challenges, including variable guide RNA activity, ensuring sufficient genome coverage, and maintaining high transformation efficiencies to ensure full library representation. These challenges are prevalent in non-conventional yeast, many of which exhibit traits that are well suited to metabolic engineering and bioprocessing. To address these hurdles in the oleaginous yeast Yarrowia lipolytica, we designed a compact, high-activity genome-wide sgRNA library. The library was designed using DeepGuide, a sgRNA activity prediction algorithm and a large dataset of ∼50,000 sgRNAs with known activity. Three guides per gene enables redundant targeting of 98.8% of genes in the genome in a library of 23,900 sgRNAs. We deployed the optimized library to uncover genes essential to the tolerance of acetate, a promising alternative carbon source, and various hydrocarbons present in many waste streams. Our screens yielded several gene knockouts that improve acetate tolerance on their own and as double knockouts in media containing acetate as the sole carbon source. Analysis of the hydrocarbon screens revealed genes related to fatty acid and alkane metabolism in Y. lipolytica. The optimized CRISPR gRNA library and its successful use in Y. lipolytica led to the discovery of alternative carbon source-related genes and provides a workflow for creating high-activity, compact genome-wide libraries for strain engineering.

中文翻译:


优化的全基因组 CRISPR 筛选能够快速改造解脂耶氏酵母中基于生长的表型



CRISPR-Cas9 功能基因组筛选揭示了与各种表型相关的基因靶标,用于代谢工程,效率极高。然而,这些全基因组筛选面临着许多设计挑战,包括可变引导RNA活性、确保足够的基因组覆盖率以及保持高转化效率以确保完整的文库表达。这些挑战在非常规酵母中普遍存在,其中许多酵母表现出非常适合代谢工程和生物加工的特性。为了解决产油酵母解脂耶氏酵母中的这些障碍,我们设计了一个紧凑的、高活性的全基因组 sgRNA 文库。该文库是使用 DeepGuide(一种 sgRNA 活性预测算法)和约 50,000 个具有已知活性的 sgRNA 的大型数据集设计的。每个基因三个向导可以冗余靶向 23,900 个 sgRNA 文库中基因组中 98.8% 的基因。我们部署了优化的文库来发现对醋酸盐(一种有前途的替代碳源)和许多废物流中存在的各种碳氢化合物的耐受性至关重要的基因。我们的筛选产生了几种基因敲除,这些基因敲除本身可以提高乙酸盐耐受性,并且在含有乙酸盐作为唯一碳源的培养基中作为双重敲除。碳氢化合物筛选分析揭示了解脂耶氏酵母中与脂肪酸和烷烃代谢相关的基因。优化的 CRISPR gRNA 文库及其在解脂耶氏酵母中的成功使用导致了替代碳源相关基因的发现,并为创建用于菌株工程的高活性、紧凑的全基因组文库提供了工作流程。
更新日期:2024-09-13
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