Functional Genomics Using the Saccharomyces cerevisiae Yeast Deletion Collections

CRISPR-Cas9 knockout screen informs efficient reduction of the Komagataella phaffii secretome

BACKGROUND

The yeast Komagataella phaffii is widely used for manufacturing recombinant proteins, but secreted titers of recombinant proteins could be improved by genetic engineering. In this study, we hypothesized that cellular resources could be redirected from production of endogenous proteins to production of recombinant proteins by deleting unneeded endogenous proteins. In non-model microorganisms such as K. phaffii, however, genetic engineering is limited by lack gene annotation and knowledge of gene essentiality.

RESULTS

We identified a set of endogenous secreted proteins in K. phaffii by mass spectrometry and signal peptide prediction. Our efforts to disrupt these genes were hindered by limited annotation of essential genes. To predict essential genes, therefore, we designed, transformed, and sequenced a pooled library of guide RNAs for CRISPR-Cas9-mediated knockout of all endogenous secreted proteins. We then used predicted gene essentiality to guide iterative disruptions of up to 11 non-essential genes. Engineered strains exhibited a ~20× increase in the production of human serum albumin and a twofold increase in the production of a monoclonal antibody.

CONCLUSIONS

We demonstrated that disruption of as few as six genes can increase production of recombinant proteins. Further reduction of the endogenous proteome of K. phaffii may further improve strain performance. The pooled library of secretome-targeted guides for CRISPR-Cas9 and knowledge of gene essentiality reported here will facilitate future efforts to engineer K. phaffii for production of other recombinant proteins and enzymes.

Using population selection and sequencing to characterize natural variation of starvation resistance in C. elegans

Starvation resistance is important to disease and fitness, but the genetic basis of its natural variation is unknown. Uncovering the genetic basis of complex, quantitative traits such as starvation resistance is technically challenging. We developed a synthetic-population (re)sequencing approach using molecular inversion probes (MIP-seq) to measure relative fitness during and after larval starvation in C. elegans. We applied this competitive assay to 100 genetically diverse, sequenced, wild strains, revealing natural variation in starvation resistance. We confirmed that the most starvation-resistant strains survive and recover from starvation better than the most starvation-sensitive strains using standard assays. We performed genome-wide association (GWA) with the MIP-seq trait data and identified three quantitative trait loci (QTL) for starvation resistance, and we created near isogenic lines (NILs) to validate the effect of these QTL on the trait. These QTL contain numerous candidate genes including several members of the Insulin/EGF Receptor-L Domain (irld) family. We used genome editing to show that four different irld genes have modest effects on starvation resistance. Natural variants of irld-39 and irld-52 affect starvation resistance, and increased resistance of the irld-39; irld-52 double mutant depends on daf-16/FoxO. DAF-16/FoxO is a widely conserved transcriptional effector of insulin/IGF signaling (IIS), and these results suggest that IRLD proteins modify IIS, though they may act through other mechanisms as well. This work demonstrates efficacy of using MIP-seq to dissect a complex trait and it suggests that irld genes are natural modifiers of starvation resistance in C. elegans.