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Yeast. 2018 Apr;35(4):331-341. doi: 10.1002/yea.3298. Epub 2018 Jan 29.

Understanding the metabolic burden of recombinant antibody production in Saccharomyces cerevisiae using a quantitative metabolomics approach.

Author information

1
Department of Bioproducts and Biosystems, School of Chemical Engineering, Aalto University, Finland, Kemistintie 1, 02150, Espoo, Finland.
2
Metabolomics Unit, Institute for Molecular Medicine Finland FIMM, University of Helsinki, Tukholmankatu 8U, Helsinki, Finland.

Abstract

The cellular changes induced by heterologous protein expression in the yeast Saccharomyces cerevisiae have been analysed on many levels and found to be significant. However, even though high-level protein production poses a metabolic burden, evaluation of the expression host at the level of the metabolome has often been neglected. We present a comparison of metabolite profiles of a wild-type strain with those of three strains producing recombinant antibody variants of increasing size and complexity: an scFv fragment, an scFv-Fc fusion protein and a full-length IgG molecule. Under producing conditions, all three recombinant strains showed a clear decrease in growth rate compared with the wild-type strain and the severity of the growth phenotype increased with size of the protein. The levels of 76 intracellular metabolites were determined using a targeted (semi) quantitative mass spectrometry based approach. Based on unsupervised and supervised multivariate analysis of metabolite profiles, together with pathway activity profiling, the recombinant strains were found to be significantly different from each other and from the wild-type strain. We observed the most prominent changes in metabolite levels for metabolites involved in amino acid and redox metabolism. Induction of the unfolded protein response was detected in all producing strains and is considered to be a contributing factor to the overall metabolic burden on the cells.

KEYWORDS:

antibody; metabolic burden; recombinant protein production; targeted metabolomics

PMID:
29159981
DOI:
10.1002/yea.3298
[Indexed for MEDLINE]
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