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Exploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach.

ABSTRACT: Brain cancers demonstrate a complex metabolic behavior so as to adapt the external hypoxic environment and internal stress generated by reactive oxygen species. To survive in these stringent conditions, glioblastoma cells develop an antagonistic metabolic phenotype as compared to their predecessors, the astrocytes, thereby quenching the resources expected for nourishing the neurons. The complexity and cumulative effect of the large scale metabolic functioning of glioblastoma is mostly unexplored. In this study, we reconstruct a metabolic network comprising of pathways that are known to be deregulated in glioblastoma cells as compared to the astrocytes. The network, consisted of 147 genes encoding for enzymes performing 247 reactions distributed across five distinct model compartments, was then studied using constrained-based modeling approach by recreating the scenarios for astrocytes and glioblastoma, and validated with available experimental evidences. From our analysis, we predict that glycine requirement of the astrocytes are mostly fulfilled by the internal glycine-serine metabolism, whereas glioblastoma cells demand an external uptake of glycine to utilize it for glutathione production. Also, cystine and glucose were identified to be the major contributors to glioblastoma growth. We also proposed an extensive set of single and double lethal reaction knockouts, which were further perturbed to ascertain their role as probable chemotherapeutic targets. These simulation results suggested that, apart from targeting the reactions of central carbon metabolism, knockout of reactions belonging to the glycine-serine metabolism effectively reduce glioblastoma growth. The combinatorial targeting of glycine transporter with any other reaction belonging to glycine-serine metabolism proved lethal to glioblastoma growth.

SUBMITTER: Bhowmick R

PROVIDER: S-EPMC5383796 | biostudies-literature | 2015 Dec

REPOSITORIES: biostudies-literature

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Exploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach.

Bhowmick Rupa R Subramanian Abhishek A Sarkar Ram Rup RR

Systems and synthetic biology 20151013 4

Brain cancers demonstrate a complex metabolic behavior so as to adapt the external hypoxic environment and internal stress generated by reactive oxygen species. To survive in these stringent conditions, glioblastoma cells develop an antagonistic metabolic phenotype as compared to their predecessors, the astrocytes, thereby quenching the resources expected for nourishing the neurons. The complexity and cumulative effect of the large scale metabolic functioning of glioblastoma is mostly unexplored ...[more]

PMID: 28392849

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Project description:BackgroundIn recent years, constrained optimization - usually referred to as flux balance analysis (FBA) - has become a widely applied method for the computation of stationary fluxes in large-scale metabolic networks. The striking advantage of FBA as compared to kinetic modeling is that it basically requires only knowledge of the stoichiometry of the network. On the other hand, results of FBA are to a large degree hypothetical because the method relies on plausible but hardly provable optimality principles that are thought to govern metabolic flux distributions.ResultsTo augment the reliability of FBA-based flux calculations we propose an additional side constraint which assures thermodynamic realizability, i.e. that the flux directions are consistent with the corresponding changes of Gibb's free energies. The latter depend on metabolite levels for which plausible ranges can be inferred from experimental data. Computationally, our method results in the solution of a mixed integer linear optimization problem with quadratic scoring function. An optimal flux distribution together with a metabolite profile is determined which assures thermodynamic realizability with minimal deviations of metabolite levels from their expected values. We applied our novel approach to two exemplary metabolic networks of different complexity, the metabolic core network of erythrocytes (30 reactions) and the metabolic network iJR904 of Escherichia coli (931 reactions). Our calculations show that increasing network complexity entails increasing sensitivity of predicted flux distributions to variations of standard Gibb's free energy changes and metabolite concentration ranges. We demonstrate the usefulness of our method for assessing critical concentrations of external metabolites preventing attainment of a metabolic steady state.ConclusionOur method incorporates the thermodynamic link between flux directions and metabolite concentrations into a practical computational algorithm. The weakness of conventional FBA to rely on intuitive assumptions about the reversibility of biochemical reactions is overcome. This enables the computation of reliable flux distributions even under extreme conditions of the network (e.g. enzyme inhibition, depletion of substrates or accumulation of end products) where metabolite concentrations may be drastically altered.

Dataset Information

Exploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach.

Publications

Exploring the differences in metabolic behavior of astrocyte and glioblastoma: a flux balance analysis approach.

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