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Titlebook: Metabolic Flux Analysis in Eukaryotic Cells; Methods and Protocol Deepak Nagrath Book 2020 Springer Science+Business Media, LLC, part of Sp

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Robust Analytical Methods for the Accurate Quantification of the Total Biomass Composition of Mammas often rely on generic data for biomass composition, e.g. collected from similar organisms. This leads to inaccurate predictions, because biomass composition varies between different cell lines, conditions, and growth phases. In this chapter we present protocols for the determination of the biomass
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Quantifying Metabolic Transfer Mediated by Extracellular Vesicles Using Exo-MFA: An Integrated Empi DNA, RNA, miRNA, and, most recently, metabolites. These particles can travel through the intercellular space and bloodstream to have regulatory effects on distant recipients. When an EV reaches a target cell, it is taken up and degraded to release its contents for utilization within the cell. In ad
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Inferring Metabolic Flux from Time-Course Metabolomics,ell differentiation and proliferation. While experimental tools like time-course metabolomics and flux tracing can measure the dynamics of a few pathways, they are unable to infer fluxes at the whole network level. To address this limitation, we have developed the Dynamic Flux Activity (DFA) algorit
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Metabolic Network Reconstructions to Predict Drug Targets and Off-Target Effects, methods, such as the use of metabolic network reconstructions, may provide a cost-effective platform to test new hypotheses for drug targets and prevent off-target effects. Here, we summarize available methods to identify drug targets and off-target effects using either reaction-centric, gene-centr
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