Quantitative prediction of cellular metabolism with constraint-based models: the COBRA Toolbox v2.0
Jan Schellenberger,Richard Que,Ronan M. T. Fleming,Ines Thiele,Jeffrey D. Orth,Adam M. Feist,Daniel C. Zielinski,Aarash Bordbar,Nathan E. Lewis,Sorena Rahmanian,Joseph Kang,Daniel R. Hyduke,Bernhard O. Palsson +12 more
TLDR
The constraint-based reconstruction and analysis toolbox as discussed by the authors is a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraintbased approach and allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules.Abstract:
The manner in which microorganisms utilize their metabolic processes can be predicted using constraint-based analysis of genome-scale metabolic networks. Herein, we present the constraint-based reconstruction and analysis toolbox, a software package running in the Matlab environment, which allows for quantitative prediction of cellular behavior using a constraint-based approach. Specifically, this software allows predictive computations of both steady-state and dynamic optimal growth behavior, the effects of gene deletions, comprehensive robustness analyses, sampling the range of possible cellular metabolic states and the determination of network modules. Functions enabling these calculations are included in the toolbox, allowing a user to input a genome-scale metabolic model distributed in Systems Biology Markup Language format and perform these calculations with just a few lines of code. The results are predictions of cellular behavior that have been verified as accurate in a growing body of research. After software installation, calculation time is minimal, allowing the user to focus on the interpretation of the computational results.read more
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Identification of a critical determinant that enables efficient fatty acid synthesis in oleaginous fungi
Haiqin Chen,Guangfei Hao,Lei Wang,Hongchao Wang,Hongchao Wang,Zhennan Gu,Liming Liu,Hao Zhang,Hao Zhang,Wei Chen,Wei Chen,Yong Q. Chen,Yong Q. Chen,Yong Q. Chen +13 more
TL;DR: It is demonstrated, for the first time, that the PPP plays a significant role during fungal lipogenesis and up-regulation of NADPH production by the P PP, especially G6PD, may be one of the critical determinants that enables efficiently fatty acid synthesis in oleaginous microbes.
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A metabolic core model elucidates how enhanced utilization of glucose and glutamine, with enhanced glutamine-dependent lactate production, promotes cancer cell growth: The WarburQ effect.
Chiara Damiani,Riccardo Colombo,Daniela Gaglio,Fabrizia Mastroianni,Dario Pescini,Hans V. Westerhoff,Hans V. Westerhoff,Hans V. Westerhoff,Giancarlo Mauri,Marco Vanoni,Lilia Alberghina +10 more
TL;DR: Simulation results offer new understanding of the logic of the metabolic reprogramming that underlies cancer cell growth and validate computational results through an extension of Flux Balance Analysis that allows prediction of metabolite variations.
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Multidisciplinary approaches for studying rhizobium-legume symbioses.
George C. diCenzo,Maryam Zamani,Alice Checcucci,Marco Fondi,Joel S. Griffitts,Turlough M. Finan,Alessio Mengoni +6 more
TL;DR: This review summarizes many of the research strategies that have been employed in the study of rhizobia and the unique knowledge gained from these diverse tools, with a focus on genome- and systems-level approaches.
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Optimal flux spaces of genome-scale stoichiometric models are determined by a few subnetworks
TL;DR: CoPE-FBA simplifies the biological interpretation of stoichiometric models of metabolism, and provides a profound understanding of metabolic flexibility in optimal states.
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The central role of the host cell in symbiotic nitrogen metabolism.
TL;DR: Host cell-mediated nitrogen recycling may be general among insect symbioses with shared EAA biosynthetic pathways generated by the loss of symbiont genes mediating terminal reactions in EAA synthesis.
References
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TL;DR: Because digenic interactions are common in yeast, similar networks may underlie the complex genetics associated with inherited phenotypes in other organisms.