Systems biology of protein synthesis and secretion in yeast
Doctoral thesis, 2021
In this thesis, we mainly use two recombinant proteins, α-amylase and insulin precursor, as model proteins to study the protein synthesis and secretion process in a model organism Saccharomyces cerevisiae. We find that the central metabolism is reprogrammed at a large scale to relieve the oxidative stress caused by recombinant protein production, and the activation of Gcn2p-mediated signaling pathway plays a crucial role in reshaping metabolism. As protein folding is often considered the flux controlling step in protein synthesis and secretion, we further identify two routes of the protein folding pathway to improve protein production, namely through improved folding capacity and increased folding precision, respectively. Additionally, protein translation is the initial step of protein synthesis. We find that cells maintain large and unequally distributed reserves in translational capacity by stepwise reducing nitrogen availability. Moreover, we also construct a proteome-constrained genome-scale protein secretory model for S. cerevisiae (pcSecYeast) to perform secretory simulations and provide genomic targets for cell engineering. Our findings elucidate the global responses to various perturbations on protein synthesis and secretion and provide valuable novel insights that can be leveraged for improving recombinant protein production.
recombinant protein production
Chalmers, Biology and Biological Engineering, Systems and Synthetic Biology
Qi Qi, Feiran Li, Egor Vorontsov, Jens Nielsen. Recombinant protein production requires metabolic reprogramming to provide more NADPH via activation of kinase Gcn2p.
Different routes of protein folding contribute to improved protein production in saccharomyces cerevisiae
mBio,; Vol. 11(2020)p. 1-12
Nitrogen limitation reveals large reserves in metabolic and translational capacities of yeast
Nature Communications,; Vol. 11(2020)
Feiran Li, Yu Chen*, Qi Qi*, Yanyan Wang*, Le Yuan, Ibrahim EI-Semman, Amir Feizi, Eduard Kerkhoven, Jens Nielsen. Genome-scale modeling of the protein secretory pathway reveals novel targets for improved recombinant protein production in yeast.
In addition, the production of recombinant proteins, including industrial enzymes, biopharmaceuticals and antibodies, is an important component in the current biotech industry. A global understanding of the protein synthesis and secretion process would contribute to the identification of rate-limiting pathways in recombinant protein production, and then to improving the titer, rate and yield (TRY) in industrial settings.
In this thesis, I study the protein synthesis and secretion system of the budding yeast Saccharomyces cerevisiae, one of the most popular model organisms in biotechnology. I first investigate the cellular responses to recombinant protein production. I show that i) the central carbon metabolism is largely reshaped to relieve the oxidative stress caused by protein synthesis and secretion; ii) the activation of Gcn2p-mediated signaling pathway plays a crucial role in the metabolic reprogramming; iii) protein folding precision can be engineered to improve recombinant protein production; iv) Cwh41p plays a key role in the folding precision control. As translation is the initial step of protein synthesis, I next focus on the translation process and show that cells maintain large and unequally distributed reserves in translational capacity. Moreover, I introduce the construction of a proteome-constrained secretory model (pcSecYeast), and show its applications in evaluation of protein misfolding process and prediction of genomic targets for improving recombinant protein production.
The results presented in this thesis provide valuable novel insights into the protein synthesis and secretion system, and show that how integrative analysis of omics data can be coupled with mathematical modeling to investigate specific biological questions.
Biochemistry and Molecular Biology
Bioinformatics and Systems Biology
Biocatalysis and Enzyme Technology
Chalmers Infrastructure for Mass spectrometry
C3SE (Chalmers Centre for Computational Science and Engineering)
Doktorsavhandlingar vid Chalmers tekniska högskola. Ny serie: 5023
Chalmers University of Technology
10:an, Kemigården 4, Göteborg
Opponent: Professor Paola Branduardi, University of Milano-Bicocca, Italy