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See detailCreation and analysis of biochemical constraint-based models using the COBRA Toolbox v.3.0.
Heirendt, Laurent UL; Arreckx, Sylvain; Pfau, Thomas UL et al

in Nature protocols (2019), 14(3), 639-702

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of ... [more ▼]

Constraint-based reconstruction and analysis (COBRA) provides a molecular mechanistic framework for integrative analysis of experimental molecular systems biology data and quantitative prediction of physicochemically and biochemically feasible phenotypic states. The COBRA Toolbox is a comprehensive desktop software suite of interoperable COBRA methods. It has found widespread application in biology, biomedicine, and biotechnology because its functions can be flexibly combined to implement tailored COBRA protocols for any biochemical network. This protocol is an update to the COBRA Toolbox v.1.0 and v.2.0. Version 3.0 includes new methods for quality-controlled reconstruction, modeling, topological analysis, strain and experimental design, and network visualization, as well as network integration of chemoinformatic, metabolomic, transcriptomic, proteomic, and thermochemical data. New multi-lingual code integration also enables an expansion in COBRA application scope via high-precision, high-performance, and nonlinear numerical optimization solvers for multi-scale, multi-cellular, and reaction kinetic modeling, respectively. This protocol provides an overview of all these new features and can be adapted to generate and analyze constraint-based models in a wide variety of scenarios. The COBRA Toolbox v.3.0 provides an unparalleled depth of COBRA methods. [less ▲]

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See detail3D Cultures of Parkinson's Disease‐Specific Dopaminergic Neurons for High Content Phenotyping and Drug Testing
Bolognin, Silvia UL; Fossépré, Marie; Qing, Xiaobing et al

in Advanced Science (2018)

Parkinson's disease (PD)‐specific neurons, grown in standard 2D cultures, typically only display weak endophenotypes. The cultivation of PD patient‐specific neurons, derived from induced pluripotent stem ... [more ▼]

Parkinson's disease (PD)‐specific neurons, grown in standard 2D cultures, typically only display weak endophenotypes. The cultivation of PD patient‐specific neurons, derived from induced pluripotent stem cells carrying the LRRK2‐G2019S mutation, is optimized in 3D microfluidics. The automated image analysis algorithms are implemented to enable pharmacophenomics in disease‐relevant conditions. In contrast to 2D cultures, this 3D approach reveals robust endophenotypes. High‐content imaging data show decreased dopaminergic differentiation and branching complexity, altered mitochondrial morphology, and increased cell death in LRRK2‐G2019S neurons compared to isogenic lines without using stressor agents. Treatment with the LRRK2 inhibitor 2 (Inh2) rescues LRRK2‐G2019S‐dependent dopaminergic phenotypes. Strikingly, a holistic analysis of all studied features shows that the genetic background of the PD patients, and not the LRRK2‐G2019S mutation, constitutes the strongest contribution to the phenotypes. These data support the use of advanced in vitro models for future patient stratification and personalized drug development. [less ▲]

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