@phdthesis{HashemiRanjbar2023,
  author    = {Hashemi Ranjbar, Seirana},
  title     = {Plasticity and trade-offs in plant metabolic networks},
  school      = {Universit{\"a}t Potsdam},
  pages     = {112},
  year      = {2023},
  abstract  = {A biological trade-off situation denotes the dependence between traits whereby an increase in the value of one of the traits leads to a decrease in the value of at least one of the others. Understanding trade-offs in cellular systems is relevant to understanding the limits and constraints to tuning desired phenotypes. Therefore, it is mainly the case for rates (i.e. fluxes) of biochemical reactions that shape not only molecular traits, like metabolite concentrations but also determine physiological traits, like growth. Intracellular fluxes are the final phenotype from transcriptional and (post)translational regulation. Quantifying intracellular fluxes provides insights into cellular physiology under particular growth conditions and can be used to characterize the metabolic activity of different pathways. However, estimating fluxes from labelling experiments is labour-intensive; therefore, developing approaches to accurately and precisely predict intracellular fluxes is essential. This thesis addresses two main problems: (i) identifying flux trade-offs and (ii) predicting accurate and precise reaction flux at a genome-scale level. To this end, the concept of an absolute flux trade-off is defined, and a constraint-based approach, termed FluTO, was developed to identify absolute flux trade-offs. FluTO is cast as a mixed integer programming approach applied to genome-scale metabolic models of E. coli, S. cerevisiae, and A. thaliana, imposing realistic constraints on growth and nutrient uptake.. The findings showed that trade-offs are not only species-specific but also specific to carbon sources. In addition, we found that different models of a single species have a different number of reactions in trade-offs. We also showed that absolute flux trade-offs depend on the biomass reaction used to model the growth of A. thaliana under different carbon and nitrogen conditions. Findings reflect the strong relation between nitrogen, carbon, and sulphur metabolisms in the leaves of C3 plants. The concept of relative trade-offs was introduced to further study trade-offs in metabolic networks. A constraint-based approach, FluTOr, was proposed to identify reactions whose fluxes are in relative trade-off concerning an optimized fitness-related cellular task, like growth. FluTOr was employed to find the relative flux trade-offsin the genome-scale metabolic networks of E. coli, S. cerevisiae, and A. thaliana. The results showed that in contrast to the A. thaliana model, the relative trade-offs in the two microorganisms depend on the carbon source, reflecting the differences in the underlying metabolic network. Furthermore, applying FluTOr also showed that reactions that participated in relative trade-offs were implicated in cofactor biosynthesis in the two microorganisms. Prediction of reaction fluxes in the constraint-based metabolic framework is usually performed by parsimonious flux balance analysis (pFBA), employing the principle of efficient usage of protein resources. However, we argued that principles related to the coordination of flux values, neglected in previous studies, provide other means to predict intracellular fluxes. To this end, we designed a constraint-based approach, termed complex-balanced FBA (cbFBA), to predict steady-state flux distributions that maximize the number of balanced complexes in a flux distribution, whereby multi-reaction dependencies are maximized. The comparative analysis showed a better agreement of the flux distributions resulting from cbFBA compared to pFBA with experimentally measured fluxes from 17 E. coli strains and 26 S. cerevisiae knock-out mutants. The results also showed that the predictions from cbFBA are more precise than those from pFBA since cbFBA results in a smaller space of alternative solutions than pFBA.},
  language  = {en}
}
@article{HashemiRazaghiMoghadamNikoloski2021,
  author    = {Hashemi, Seirana and Razaghi-Moghadam, Zahra and Nikoloski, Zoran},
  title     = {Identification of flux trade-offs in metabolic networks},
  series = {Scientific reports},
  volume    = {11},
  journal   = {Scientific reports},
  number    = {1},
  publisher = {Macmillan Publishers Limited, part of Springer Nature},
  address   = {London},
  issn      = {2045-2322},
  doi       = {10.1038/s41598-021-03224-9},
  pages     = {10},
  year      = {2021},
  abstract  = {Trade-offs are inherent to biochemical networks governing diverse cellular functions, from gene expression to metabolism. Yet, trade-offs between fluxes of biochemical reactions in a metabolic network have not been formally studied. Here, we introduce the concept of absolute flux trade-offs and devise a constraint-based approach, termed FluTO, to identify and enumerate flux trade-offs in a given genome-scale metabolic network. By employing the metabolic networks of Escherichia coli and Saccharomyces cerevisiae, we demonstrate that the flux trade-offs are specific to carbon sources provided but that reactions involved in the cofactor and prosthetic group biosynthesis are present in trade-offs across all carbon sources supporting growth. We also show that absolute flux trade-offs depend on the biomass reaction used to model the growth of Arabidopsis thaliana under different carbon and nitrogen conditions. The identified flux trade-offs reflect the tight coupling between nitrogen, carbon, and sulphur metabolisms in leaves of C-3 plants. Altogether, FluTO provides the means to explore the space of alternative metabolic routes reflecting the constraints imposed by inherent flux trade-offs in large-scale metabolic networks.},
  language  = {en}
}