We investigate the impact of droplet culture conditions on cell metabolic state by determining key metabolite concentrations in S. cerevisiae cultures in different microfluidic droplet culture formats. Control of culture conditions is critical for single cell/clone screening in droplets, such as directed evolution of yeast, as cell metabolic state directly affects production yields from cell factories. Here, we analyze glucose, pyruvate, ethanol, and glycerol, central metabolites in yeast glucose dissimilation to establish culture formats for screening of respiring as well as fermenting yeast. Metabolite profiling provides a more nuanced estimate of cell state compared to proliferation studies alone. We show that the choice of droplet incubation format impacts cell proliferation and metabolite production. The standard syringe incubation of droplets exhibited metabolite profiles similar to oxygen limited cultures, whereas the metabolite profiles of cells cultured in the alternative wide tube droplet incubation format resemble those from aerobic culture. Furthermore, we demonstrate retained droplet stability and size in the new better oxygenated droplet incubation format.

The cellular machinery that supports protein synthesis and secretion lies at the foundation of cell factory-centered protein production. Due to the complexity of such cellular machinery, the challenge in generating a superior cell factory is to fully exploit the production potential by finding beneficial targets for optimized strains, which ideally could be used for improved secretion of other proteins. We focused on an approach in the yeast Saccharomyces cerevisiae that allows for attenuation of gene expression, using RNAi combined with high-throughput microfluidic single-cell screening for cells with improved protein secretion. Using direct experimental validation or enrichment analysis-assisted characterization of systematically introduced RNAi perturbations, we could identify targets that improve protein secretion. We found that genes with functions in cellular metabolism (YDC1, AAD4, ADE8, and SDH1), protein modification and degradation (VPS73, KTR2, CNL1, and SSA1), and cell cycle (CDC39), can all impact recombinant protein production when expressed at differentially down regulated levels. By establishing a workflow that incorporates Cas9-mediated recombineering, we demonstrated how we could tune the expression of the identified gene targets for further improved protein production for specific proteins. Our findings offer a high throughput and semirational platform design, which will improve not only the production of a desired protein but even more importantly, shed additional light on connections between protein production and other cellular processes.