Microfluidic screening and whole-genome sequencing identifies mutations associated with improved protein secretion by yeast
Journal article, 2015

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.

droplet microfluidics

protein secretion

systems biology

yeast cell factories

random mutagenesis

Author

Mingtao Huang

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Y. Bai

Royal Institute of Technology (KTH)

East China University of Science and Technology

S. L. Sjostrom

Royal Institute of Technology (KTH)

B. M. Hallstrom

Royal Institute of Technology (KTH)

Zihe Liu

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Dina Petranovic Nielsen

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

M. Uhlen

Royal Institute of Technology (KTH)

Technical University of Denmark (DTU)

H. N. Joensson

Royal Institute of Technology (KTH)

H. A. Svahn

Royal Institute of Technology (KTH)

Jens B Nielsen

Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology

Proceedings of the National Academy of Sciences of the United States of America

0027-8424 (ISSN) 1091-6490 (eISSN)

Vol. 112 34 E4689-E4696

Industrial Systems Biology of Yeast and A. oryzae (INSYSBIO)

European Commission (FP7), 2010-01-01 -- 2014-12-31.

Areas of Advance

Life Science Engineering (2010-2018)

Subject Categories

Bioinformatics and Systems Biology

DOI

10.1073/pnas.1506460112

PubMed

26261321

More information

Latest update

2/28/2018