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bioRxiv · 10.1101/2022.05.04.490403

A computational toolbox to investigate the metabolic potential and resource allocation in fission yeast

Grigaitis, P.·Grundel, D. A. J.·van Pelt-KleinJan, E.·Isaku, M.·Xie, G.·Mendoza Farias, S.·Teusink, B.·van Heerden, J. H.
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Abstract

The fission yeast Schizosaccharomyces pombe is a popular eukaryal model organism for cell division and cell cycle studies. With this extensive knowledge of its cell and molecular biology, S. pombe also holds promise for use in metabolism research and industrial applications. However, unlike the bakers yeast Saccharomyces cerevisiae, a major workhorse in these areas, cell physiology and metabolism of S. pombe remain less explored. One way to advance understanding of organism-specific metabolism is construction of computational models and their use for hypothesis testing. To this end, we leverage existing knowledge of S. cerevisiae to generate a manually-curated high-quality reconstruction of S. pombes metabolic network, including a proteome-constrained version of the model. Using these models, we gain insights into the energy demands for growth, as well as ribosome kinetics in S. pombe. Furthermore, we predict proteome composition and identify growth-limiting constraints that determine optimal metabolic strategies under different glucose availability regimes, and reproduce experimentally determined metabolic profiles. Notably, we find similarities in metabolic and proteome predictions of S. pombe with S. cerevisiae, which indicate that similar cellular resource constraints operate to dictate metabolic organization. With these use cases, we show, on the one hand, how these models provide an efficient means to transfer metabolic knowledge from a well-studied to a lesser-studied organism, and on the other, how they can successfully be used to explore the metabolic behaviour and the role of resource allocation in driving different strategies in fission yeast.

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Grigaitis, P., Grundel, D. A. J., van Pelt-KleinJan, E., Isaku, M., Xie, G., Mendoza Farias, S., Teusink, B., van Heerden, J. H.. 2022-05-04. A computational toolbox to investigate the metabolic potential and resource allocation in fission yeast. https://doi.org/10.1101/2022.05.04.490403

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