One-step multiple gene disruption in the model organism Saccharomyces cerevisiae is a highly useful tool for both basic and applied research, but it remains a challenge. Here, we report a rapid, efficient, and potentially scalable strategy based on the type II Clustered Regularly Interspaced Short Palindromic Repeats (CRISPR)-CRISPR associated proteins (Cas) system to generate multiple gene disruptions simultaneously in S. cerevisiae. A 100 bp dsDNA mutagenizing homologous recombination donor is inserted between two direct repeats for each target gene in a CRISPR array consisting of multiple donor and guide sequence pairs. An ultrahigh copy number plasmid carrying iCas9, a variant of wild-type Cas9, trans-encoded RNA (tracrRNA), and a homology-integrated crRNA cassette is designed to greatly increase the gene disruption efficiency. As proof of concept, three genes, CAN1, ADE2, and LYP1, were simultaneously disrupted in 4 days with an efficiency ranging from 27 to 87%. Another three genes involved in an artificial hydrocortisone biosynthetic pathway, ATF2, GCY1, and YPR1, were simultaneously disrupted in 6 days with 100% efficiency. This homology-integrated CRISPR (HI-CRISPR) strategy represents a powerful tool for creating yeast strains with multiple gene knockouts.
A major challenge in metabolic engineering and synthetic biology is to balance the flux of an engineered heterologous metabolic pathway to achieve high yield and productivity in a target organism. Here, we report a simple, efficient and programmable approach named ‘customized optimization of metabolic pathways by combinatorial transcriptional engineering (COMPACTER)’ for rapid tuning of gene expression in a heterologous pathway under distinct metabolic backgrounds. Specifically, a library of mutant pathways is created by de novo assembly of promoter mutants of varying strengths for each pathway gene in a target organism followed by high-throughput screening/selection. To demonstrate this approach, a single round of COMPACTER was used to generate both a xylose utilizing pathway with near-highest efficiency and a cellobiose utilizing pathway with highest efficiency that were ever reported in literature for both laboratory and industrial yeast strains. Interestingly, these engineered xylose and cellobiose utilizing pathways were all host-specific. Therefore, COMPACTER represents a powerful approach to tailor-make metabolic pathways for different strain backgrounds, which is difficult if not impossible to achieve by existing pathway engineering methods.
Genome-scale engineering is indispensable in understanding and engineering microorganisms, but the current tools are mainly limited to bacterial systems. Here we report an automated platform for multiplex genome-scale engineering in Saccharomyces cerevisiae, an important eukaryotic model and widely used microbial cell factory. Standardized genetic parts encoding overexpression and knockdown mutations of >90% yeast genes are created in a single step from a full-length cDNA library. With the aid of CRISPR-Cas, these genetic parts are iteratively integrated into the repetitive genomic sequences in a modular manner using robotic automation. This system allows functional mapping and multiplex optimization on a genome scale for diverse phenotypes including cellulase expression, isobutanol production, glycerol utilization and acetic acid tolerance, and may greatly accelerate future genome-scale engineering endeavours in yeast.
Engineered biological systems such as genetic circuits and microbial cell factories have promised to solve many challenges in the modern society. However, the artisanal processes of research and development are slow, expensive, and inconsistent, representing a major obstacle in biotechnology and bioengineering. In recent years, biological foundries or biofoundries have been developed to automate design-build-test engineering cycles in an effort to accelerate these processes. This review summarizes the enabling technologies for such biofoundries as well as their early successes and remaining challenges.
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