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Computational modelling of a photorespiratory bypass in C3 metabolism to establish a synthetic C4 cycle

  • Studying and understanding the metabolism of plants is essential to better adapt them to future climate conditions. Computational models of plant metabolism can guide this process by providing a platform for fast and resource-saving in silico analyses. The reconstruction of these models can follow kinetic or stoichiometric approaches with Flux Balance Analysis being one of the most common one for stoichiometric models. Advances in metabolic modelling over the years include the increasing number of compartments, the automation of the reconstruction process, the modelling of plant-environment interactions and genetic variants or temporally and spatially resolved models. In addition, there is a growing focus on introducing synthetic pathways in plants to increase their agricultural potential regarding yield, growth and nutritional value. One example is the β-hydroxyaspartate cycle (BHAC) to bypass photorespiration. After the implementation in a stoichiometric C3 plant model, in silico flux analyses can help to understand the resulting metabolic changes. When comparing with in vivo experiments with BHAC plants, the metabolic model can reproduce most results with exceptions regarding growth and oxaloacetate. To evaluate whether the BHAC is suitable to establish a synthetic C4 cycle, the pathway is implemented in a two-cell type model that is capable of running a C4 cycle. The results show that the BHAC is only beneficial under light limitation in the bundle sheath cell. An additional engineering target for improved performance of plants is malate synthase. This work serves as the basis for further analyses combining the different factors boosting the advantages of the BHAC and for in vivo experiments in C3 and C4 plants.

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Metadaten
Author:Lisa Schönherr
Advisor:Röbbe Wünschiers, Nadine Töpfer
Document Type:Bachelor Thesis
Language:English
Year of Completion:2022
Granting Institution:Hochschule Mittweida
Release Date:2022/11/23
GND Keyword:Pflanzen; Stoffwechsel
Page Number:85
Institutes:Angewandte Computer‐ und Bio­wissen­schaften
DDC classes:572.4 Stoffwechsel
Open Access:Frei zugänglich
Licence (German):License LogoUrheberrechtlich geschützt