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Genetic engineering of industrial cell lines often requires knockout of multiple endogenous genes. Tools like CRISPR-Cas9 have enabled serial or parallelized gene disruption in a wide range of industrial organisms, but common practices for the screening and validation of genome edits are lacking. For gene disruption, DNA repair by homologous recombination offers several advantages over nonhomologous end joining, including more efficient screening for knockout clones and improved genomic stability. Here we designed and characterized a knockout fragment intended to repair Cas9-induced gene disruptions by homologous recombination. We identified knockout clones of Komagataella phaffii with high fidelity by PCR, removing the need for Sanger sequencing. Short overlap sequences for homologous recombination (30 bp) enabled the generation of gene-specific knockout fragments by PCR, removing the need for subcloning. Finally, we demonstrated that the genotype conferred by the knockout fragment is stable under common cultivation conditions.

Constructing efficient cellular factories often requires integration of heterologous pathways for synthesis of novel compounds and improved cellular productivity. Few genomic sites are routinely used, however, for efficient integration and expression of heterologous genes, especially in nonmodel hosts. Here, a data-guided framework for informing suitable integration sites for heterologous genes based on ATAC-seq was developed in the nonmodel yeast Komagataella phaffii . Single-copy GFP constructs were integrated using CRISPR/Cas9 into 38 intergenic regions (IGRs) to evaluate the effects of IGR size, intensity of ATAC-seq peaks, and orientation and expression of adjacent genes. Only the intensity of accessibility peaks was observed to have a significant effect, with higher expression observed from IGRs with low- to moderate-intensity peaks than from high-intensity peaks. This effect diminished for tandem, multicopy integrations, suggesting that the additional copies of exogenous sequence buffered the transcriptional unit of the transgene against effects from endogenous sequence context. The approach developed from these results should provide a basis for nominating suitable IGRs in other eukaryotic hosts from an annotated genome and ATAC-seq data.

There is growing interest in the use of nonmodel microorganisms as hosts for biopharmaceutical manufacturing. These hosts require genomic engineering to meet clinically relevant product qualities and titers, but the adaptation of tools for editing genomes, such as CRISPR-Cas9, has been slow for poorly characterized hosts. Specifically, a lack of biochemical characterization of RNA polymerase III transcription has hindered reliable expression of guide RNAs in new hosts. Here, we present a sequencing-based strategy for the design of host-specific cassettes for modular, reliable, expression of guide RNAs. Using this strategy, we achieved up to 95% gene editing efficiency in the methylotrophic yeast Komagataella phaffii . We applied this approach for the rapid, multiplexed engineering of a complex phenotype, achieving humanized product glycosylation in two sequential steps of engineering. Reliable extension of simple gene editing tools to nonmodel manufacturing hosts will enable rapid engineering of manufacturing strains tuned for specific product profiles and potentially decrease the costs and timelines for process development.

Efforts to engineer microbial factories have benefitted from mining biological diversity and high throughput synthesis of novel enzymatic pathways, yet screening and optimizing metabolic pathways remain rate-limiting steps. Metabolite-responsive biosensors may help to address these persistent challenges by enabling the monitoring of metabolite levels in individual cells and metabolite-responsive feedback control. We are currently limited to naturally evolved biosensors, which are insufficient for monitoring many metabolites of interest. Thus, a method for engineering novel biosensors would be powerful, yet we lack a generalizable approach that enables the construction of a wide range of biosensors. As a step toward this goal, we here explore several strategies for converting a metabolite-binding protein into a metabolite-responsive transcriptional regulator. By pairing a modular protein design approach with a library of synthetic promoters and applying robust statistical analyses, we identified strategies for engineering biosensor-regulated bacterial promoters and for achieving design-driven improvements of biosensor performance. We demonstrated the feasibility of this strategy by fusing a programmable DNA binding motif (zinc finger module) with a model ligand binding protein (maltose binding protein), to generate a novel biosensor conferring maltose-regulated gene expression. This systematic investigation provides insights that may guide the development of additional novel biosensors for diverse synthetic biology applications.