Designing an optimal microbial cell factory often requires overexpression, knock-down, and knock-out of multiple gene targets. Unfortunately, such rewiring of cellular metabolism is often carried out sequentially and with low throughput. Here, we report a combinatorial metabolic engineering strategy based on an orthogonal tri-functional CRISPR system that combines transcriptional activation, transcriptional interference, and gene deletion (CRISPR-AID) in the yeast Saccharomyces cerevisiae. This strategy enables perturbation of the metabolic and regulatory networks in a modular, parallel, and high-throughput manner. We demonstrate the application of CRISPR-AID not only to increase the production of β-carotene by 3-fold in a single step, but also to achieve 2.5-fold improvement in the display of an endoglucanase on the yeast surface by optimizing multiple metabolic engineering targets in a combinatorial manner.

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.

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