TY  - JOUR
A1  - Hashemi, Seirana
A1  - Razaghi-Moghadam, Zahra
A1  - Laitinen, Roosa A. E.
A1  - Nikoloski, Zoran
T1  - Relative flux trade-offs and optimization of metabolic network functionalities
JF  - Computational and structural biotechnology journal
N2  - Trade-offs between traits are present across different levels of biological systems and ultimately reflect constraints imposed by physicochemical laws and the structure of underlying biochemical networks. Yet, mechanistic explanation of how trade-offs between molecular traits arise and how they relate to optimization of fitness-related traits remains elusive. Here, we introduce the concept of relative flux trade-offs and propose a constraint-based approach, termed FluTOr, to identify metabolic reactions whose fluxes are in relative trade-off with respect to an optimized fitness-related cellular task, like growth. We then employed FluTOr to identify relative flux trade-offs in the genome-scale metabolic networks of Escherichia coli, Saccharomyces cerevisiae, and Arabidopsis thaliana. For the metabolic models of E. coli and S. cerevisiae we showed that: (i) the identified relative flux trade-offs depend on the carbon source used and that (ii) reactions that participated in relative trade-offs in both species were implicated in cofactor biosynthesis. In contrast to the two microorganisms, the relative flux trade-offs for the metabolic model of A. thaliana did not depend on the available nitrogen sources, reflecting the differences in the underlying metabolic network as well as the considered environments. Lastly, the established connection between relative flux trade-offs allowed us to identify overexpression targets that can be used to optimize fitness-related traits. Altogether, our computational approach and findings demonstrate how relative flux trade-offs can shape optimization of metabolic tasks, important in biotechnological applications.
KW  - Trade-offs
KW  - Metabolic networks
KW  - Fluxes
KW  - Overexpression targets
KW  - Growth
Y1  - 2022
U6  - https://doi.org/10.1016/j.csbj.2022.07.038
SN  - 2001-0370
VL  - 20
SP  - 3963
EP  - 3971
PB  - Research Network of Computational and Structural Biotechnology (RNCSB)
CY  - Gotenburg
ER  - 
TY  - JOUR
A1  - Hashemi, Seirana
A1  - Razaghi-Moghadam, Zahra
A1  - Nikoloski, Zoran
T1  - Identification of flux trade-offs in metabolic networks
JF  - Scientific reports
N2  - 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.
Y1  - 2021
U6  - https://doi.org/10.1038/s41598-021-03224-9
SN  - 2045-2322
VL  - 11
IS  - 1
PB  - Macmillan Publishers Limited, part of Springer Nature
CY  - London
ER  -