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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A novel synthetic medium and expression system for subzero growth and recombinant protein production in Pseudoalteromonas haloplanktis TAC125
Filomena Sannino,Maria Giuliani,Umberto Salvatore,Gennaro Antonio Apuzzo,Donatella de Pascale,Renato Fani,Marco Fondi,Gennaro Marino,Maria Luisa Tutino,Ermenegilda Parrilli +9 more
TL;DR: A novel synthetic medium is developed, containing D-gluconate and L-glutamate, and a finely regulated gene expression system inducible by D-galactose is setup to produce recombinant protein in GG synthetic medium, thus providing an innovative strategy for the recombinant production of “difficult” proteins.
Journal ArticleDOI
Dynamic epistasis for different alleles of the same gene
TL;DR: The results indicate that epistasis among genes can be dynamically rewired at the genome level, and call on future efforts to revisit theories that can integrate epistatic dynamics among genes in biological systems.
Journal ArticleDOI
Genome-scale metabolic models of Microbacterium species isolated from a high altitude desert environment
Dinka Mandakovic,Ángela Cintolesi,Jonathan Maldonado,Sebastián N. Mendoza,Méziane Aite,Méziane Aite,Alexis Gaete,Francisco Saitua,Miguel L. Allende,Verónica Cambiazo,Anne Siegel,Anne Siegel,Alejandro Maass,Mauricio González,Mauricio Latorre +14 more
TL;DR: This study investigated whether strain-specific features of two Microbacterium species were involved in the metabolic ability to tolerate/adapt to local variations within an extreme desert environment and found significant differences in the connectivity of specific metabolites related to pH tolerance and CO2 production.
Journal ArticleDOI
Green pathways: Metabolic network analysis of plant systems
TL;DR: The present review presents a state-of-the-art toolbox for plant metabolic network analysis, including different in silico modeling techniques, including flux balance analysis, elementary flux mode analysis and kinetic flux profiling, as well as different variants of experiments with plant systems which use radioactive and stable isotopes to determine in vivo plant metabolic fluxes.
Journal ArticleDOI
Genome sequencing and biodegradation characteristics of the n-butyl benzyl phthalate degrading bacterium-Rhodococcus sp. HS-D2
TL;DR: The metabolic pathway of this bacterium needs further exploration to improve the biodegradation efficiency of BBP, and the growth rate of HS-D2 and BBP consumption rate were analyzed in silico simulation, and were found to be consistent with the rates of HS -D2 growth andBBP consumption the in vitro experiment.
References
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Global Mapping of the Yeast Genetic Interaction Network
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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.