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Genome-scale model reconstruction of the methylotrophic yeast Ogataea polymorpha

Authors
  • Liebal, Ulf W1
  • Fabry, Brigida A1
  • Ravikrishnan, Aarthi2
  • Schedel, Constantin VL1
  • Schmitz, Simone1
  • Blank, Lars M1
  • Ebert, Birgitta E1, 3, 4
  • 1 Institute of Applied Microbiology-iAMB, Aachen Biology and Biotechnology-ABBt, RWTH Aachen University, Worringer Weg 1, Aachen, 52074, Germany , Aachen (Germany)
  • 2 Genome Institute of Singapore, 60 Biopolis Street, Genome, 03-01, Singapore, 138672, Singapore , Singapore (Singapore)
  • 3 Australian Institute for Bioengineering and Nanotechnology, The University of Queensland, Brisbane, QLD 4072, Australia , Brisbane (Australia)
  • 4 CSIRO Future Science Platform in Synthetic Biology, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Black Mountain, ACT 2601, Australia , Black Mountain (Australia)
Type
Published Article
Journal
BMC Biotechnology
Publisher
Springer (Biomed Central Ltd.)
Publication Date
Mar 15, 2021
Volume
21
Issue
1
Identifiers
DOI: 10.1186/s12896-021-00675-w
Source
Springer Nature
Keywords
License
Green

Abstract

BackgroundOgataea polymorpha is a thermotolerant, methylotrophic yeast with significant industrial applications. While previously mainly used for protein synthesis, it also holds promise for producing platform chemicals. O. polymorpha has the distinct advantage of using methanol as a substrate, which could be potentially derived from carbon capture and utilization streams. Full development of the organism into a production strain and estimation of the metabolic capabilities require additional strain design, guided by metabolic modeling with a genome-scale metabolic model. However, to date, no genome-scale metabolic model is available for O. polymorpha.ResultsTo overcome this limitation, we used a published reconstruction of the closely related yeast Komagataella phaffii as a reference and corrected reactions based on KEGG and MGOB annotation. Additionally, we conducted phenotype microarray experiments to test the suitability of 190 substrates as carbon sources. Over three-quarter of the substrate use was correctly reproduced by the model and 27 new substrates were added, that were not present in the K. phaffii reference model.ConclusionThe developed genome-scale metabolic model of O. polymorpha will support the engineering of synthetic metabolic capabilities and enable the optimization of production processes, thereby supporting a sustainable future methanol economy.

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