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

Journal of Fungi, vol. 8, pp. 524

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.

Authors 7

1. Ulf W. Liebal corresponding Aachen iAMB-Institute of Applied Microbiology

   RWTH Aachen University

   Affiliation as printed

   iAMB-Institute of Applied Microbiology, ABBt, RWTH Aachen University, Worringerweg 1, 52074 Aachen, Germany

2. Lena Ullmann Aachen iAMB-Institute of Applied Microbiology

   RWTH Aachen University

   Affiliation as printed

   iAMB-Institute of Applied Microbiology, ABBt, RWTH Aachen University, Worringerweg 1, 52074 Aachen, Germany

3. Christian Lieven

   Technical University of Denmark · Novo Nordisk Foundation

   Affiliation as printed

   Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK-2800 Kgs. Lyngby, Denmark

   Unseen Biometrics ApS, DK-2800 Kgs. Lyngby, Denmark

4. Philipp Kohl Aachen iAMB-Institute of Applied Microbiology

   RWTH Aachen University

   Affiliation as printed

   iAMB-Institute of Applied Microbiology, ABBt, RWTH Aachen University, Worringerweg 1, 52074 Aachen, Germany

5. Daniel Wibberg

   Bielefeld University

   Affiliation as printed

   Genome Research of Industrial Microorganisms, CeBiTec, Bielefeld University, 33501 Bielefeld, Germany

6. Thiemo Zambanini Aachen iAMB-Institute of Applied Microbiology

   RWTH Aachen University

   Affiliation as printed

   iAMB-Institute of Applied Microbiology, ABBt, RWTH Aachen University, Worringerweg 1, 52074 Aachen, Germany

7. Lars M. Blank corresponding Aachen iAMB-Institute of Applied Microbiology

   RWTH Aachen University

   Affiliation as printed

   iAMB-Institute of Applied Microbiology, ABBt, RWTH Aachen University, Worringerweg 1, 52074 Aachen, Germany