Microfluidic screening and whole-genome sequencing identifies mutations associated with improved protein secretion by yeast

Mingtao Huang, Yunpeng Bai, Staffan L. Sjostrom, Björn M. Hallström, Zihe Liu, Dina Petranovic, Mathias Uhlén, Haakan N. Joensson, Helene Andersson Svahn, Jens Nielsen

Research output: Contribution to journalJournal articleResearchpeer-review

Abstract

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 high-throughput 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 a-amylase. Efficient secretion was genetically stable in the selected clones. We performed whole-genome 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.
Original languageEnglish
JournalProceedings of the National Academy of Sciences of the United States of America
Volume112
Issue number34
Pages (from-to)E4689-E4696
Number of pages8
ISSN0027-8424
DOIs
Publication statusPublished - 2015

Keywords

  • Protein secretion
  • Yeast cell factories
  • Droplet microfluidics
  • Random mutagenesis
  • Systems biology

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