Engineered metabolic pathways often suffer from flux imbalances that can overburden the cell and accumulate intermediate metabolites, resulting in reduced product titers. One way to alleviate such imbalances is to adjust the expression levels of the constituent enzymes using a combinatorial expression library. Typically, this approach requires high-throughput assays, which are unfortunately unavailable for the vast majority of desirable target compounds. To address this, we applied regression modeling to enable expression optimization using only a small number of measurements. We characterized a set of constitutive promoters in Saccharomyces cerevisiae that spanned a wide range of expression and maintained their relative strengths irrespective of the coding sequence. We used a standardized assembly strategy to construct a combinatorial library and express for the first time in yeast the five-enzyme violacein biosynthetic pathway. We trained a regression model on a random sample comprising 3% of the total library, and then used that model to predict genotypes that would preferentially produce each of the products in this highly branched pathway. This generalizable method should prove useful in engineering new pathways for the sustainable production of small molecules.

The directed evolution of biomolecules to improve or change their activity is central to many engineering and synthetic biology efforts. However, selecting improved variants from gene libraries in living cells requires plasmid expression systems that suffer from variable copy number effects, or the use of complex marker-dependent chromosomal integration strategies. We developed quantitative gene assembly and DNA library insertion into the Saccharomyces cerevisiae genome by optimizing an efficient single-step and marker-free genome editing system using CRISPR-Cas9. With this Multiplex CRISPR (CRISPRm) system, we selected an improved cellobiose utilization pathway in diploid yeast in a single round of mutagenesis and selection, which increased cellobiose fermentation rates by over 10-fold. Mutations recovered in the best cellodextrin transporters reveal synergy between substrate binding and transporter dynamics, and demonstrate the power of CRISPRm to accelerate selection experiments and discoveries of the molecular determinants that enhance biomolecule function.

Eukaryotic cells execute complex transcriptional programs in which specific loci throughout the genome are regulated in distinct ways by targeted regulatory assemblies. We have applied this principle to generate synthetic CRISPR-based transcriptional programs in yeast and human cells. By extending guide RNAs to include effector protein recruitment sites, we construct modular scaffold RNAs that encode both target locus and regulatory action. Sets of scaffold RNAs can be used to generate synthetic multigene transcriptional programs in which some genes are activated and others are repressed. We apply this approach to flexibly redirect flux through a complex branched metabolic pathway in yeast. Moreover, these programs can be executed by inducing expression of the dCas9 protein, which acts as a single master regulatory control point. CRISPR-associated RNA scaffolds provide a powerful way to construct synthetic gene expression programs for a wide range of applications, including rewiring cell fates or engineering metabolic pathways.