There is an increasing demand for biotech-based production of recombinant proteins for use as pharmaceuticals in the food and feed industry and in industrial applications. Yeast Saccharomyces cerevisiae is among preferred cell factories for recombinant protein production, and there is increasing interest in improving its protein secretion capacity. Due to the complexity of the secretory machinery in eukaryotic cells, it is difficult to apply rational engineering for construction of improved strains. Here we used highthroughput microfluidics for the screening of yeast libraries, generated by UV mutagenesis. Several screening and sorting rounds resulted in the selection of eight yeast clones with significantly improved secretion of recombinant α-amylase. Efficient secretion was genetically stable in the selected clones. We performed wholegenome sequencing of the eight clones and identified 330 mutations in total. Gene ontology analysis of mutated genes revealed many biological processes, including some that have not been identified before in the context of protein secretion. Mutated genes identified in this study can be potentially used for reverse metabolic engineering, with the objective to construct efficient cell factories for protein secretion. The combined use of microfluidics screening and whole-genome sequencing to map the mutations associated with the improved phenotype can easily be adapted for other products and cell types to identify novel engineering targets, and this approach could broadly facilitate design of novel cell factories.protein secretion | yeast cell factories | droplet microfluidics | random mutagenesis | systems biology T he production of recombinant proteins by cell factories, including biopharmaceutical proteins and industrial enzymes, is a growing multibillion-dollar industry (1) and demands continuous improvement of the chosen cell factories. The improvements involve optimization of transcription and translation, but also of protein posttranslational modifications, folding, and trafficking. One of the remaining challenges is the rational engineering design for the optimization of the protein secretory capacity, which involves a complex secretory network (2). The complexity of the protein secretory machinery and lack of a complete understanding of its underlying mechanisms has limited the utility of rational metabolic engineering for the improvement of recombinant protein production (3). Designing an efficient cell platform for protein secretion may often require overcoming limitations at different levels, e.g., translation, protein folding, and protein trafficking, and the modification of a single metabolic engineering target may therefore be insufficient (4). Although adaptive laboratory evolution has proven a useful strategy to acquire desired phenotypes with accumulation of beneficial mutations under selective pressure (5), this approach can be more cumbersome when trying to select clones with improved protein secretion.Alternatively, a cell library can be constructed by introduci...