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Article

Ustilago maydis Metabolic Characterization and Growth Quantification with a Genome-Scale Metabolic Model

by
Ulf W. Liebal
1,*,
Lena Ullmann
1,
Christian Lieven
2,3,
Philipp Kohl
1,
Daniel Wibberg
4,†,
Thiemo Zambanini
1 and
Lars M. Blank
1,*
1
iAMB-Institute of Applied Microbiology, ABBt, RWTH Aachen University, Worringerweg 1, 52074 Aachen, Germany
2
Unseen Biometrics ApS, DK-2800 Kgs. Lyngby, Denmark
3
Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark
4
Genome Research of Industrial Microorganisms, CeBiTec, Bielefeld University, 33501 Bielefeld, Germany
*
Authors to whom correspondence should be addressed.
†
Current address: Institute of Bio- and Geosciences IBG-5, Computational Metagenomics, Forschungszentrum Jülich GmbH, 52425 Jülich, Germany.
J. Fungi 2022, 8(5), 524; https://doi.org/10.3390/jof8050524
Submission received: 24 March 2022 / Revised: 16 May 2022 / Accepted: 17 May 2022 / Published: 20 May 2022
(This article belongs to the Special Issue Smut Fungi 2.0)
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Abstract

Ustilago maydis is an important plant pathogen that causes corn smut disease and serves as an effective biotechnological production host. The lack of a comprehensive metabolic overview hinders a full understanding of the organism’s environmental adaptation and a full use of its metabolic potential. Here, we report the first genome-scale metabolic model (GSMM) of Ustilago maydis (iUma22) for the simulation of metabolic activities. iUma22 was reconstructed from sequencing and annotation using PathwayTools, and the biomass equation was derived from literature values and from the codon composition. The final model contains over 25% annotated genes (6909) in the sequenced genome. Substrate utilization was corrected by BIOLOG phenotype arrays, and exponential batch cultivations were used to test growth predictions. The growth data revealed a decrease in glucose uptake rate with rising glucose concentration. A pangenome of four different U. maydis strains highlighted missing metabolic pathways in iUma22. The new model allows for studies of metabolic adaptations to different environmental niches as well as for biotechnological applications.
Keywords: Ustilago maydis; genome-scale metabolic model; constraint-based model; biotechnology; COBRA; FBA; metabolism; itaconate Ustilago maydis; genome-scale metabolic model; constraint-based model; biotechnology; COBRA; FBA; metabolism; itaconate

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MDPI and ACS Style

Liebal, U.W.; Ullmann, L.; Lieven, C.; Kohl, P.; Wibberg, D.; Zambanini, T.; Blank, L.M. Ustilago maydis Metabolic Characterization and Growth Quantification with a Genome-Scale Metabolic Model. J. Fungi 2022, 8, 524. https://doi.org/10.3390/jof8050524

AMA Style

Liebal UW, Ullmann L, Lieven C, Kohl P, Wibberg D, Zambanini T, Blank LM. Ustilago maydis Metabolic Characterization and Growth Quantification with a Genome-Scale Metabolic Model. Journal of Fungi. 2022; 8(5):524. https://doi.org/10.3390/jof8050524

Chicago/Turabian Style

Liebal, Ulf W., Lena Ullmann, Christian Lieven, Philipp Kohl, Daniel Wibberg, Thiemo Zambanini, and Lars M. Blank. 2022. "Ustilago maydis Metabolic Characterization and Growth Quantification with a Genome-Scale Metabolic Model" Journal of Fungi 8, no. 5: 524. https://doi.org/10.3390/jof8050524

APA Style

Liebal, U. W., Ullmann, L., Lieven, C., Kohl, P., Wibberg, D., Zambanini, T., & Blank, L. M. (2022). Ustilago maydis Metabolic Characterization and Growth Quantification with a Genome-Scale Metabolic Model. Journal of Fungi, 8(5), 524. https://doi.org/10.3390/jof8050524

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