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Metabolic characterization of cultured mammalian cells by mass balance analysis, tracer labeling experiments and computer-aided simulations

Paper ID Volume ID Publish Year Pages File Format Full-Text
20065 43155 2015 7 PDF Available
Title
Metabolic characterization of cultured mammalian cells by mass balance analysis, tracer labeling experiments and computer-aided simulations
Abstract

Studying metabolic directions and flow rates in cultured mammalian cells can provide key information for understanding metabolic function in the fields of cancer research, drug discovery, stem cell biology, and antibody production. In this work, metabolic engineering methodologies including medium component analysis, 13C-labeling experiments, and computer-aided simulation analysis were applied to characterize the metabolic phenotype of soft tissue sarcoma cells derived from p53-null mice. Cells were cultured in medium containing [1-13C] glutamine to assess the level of reductive glutamine metabolism via the reverse reaction of isocitrate dehydrogenase (IDH). The specific uptake and production rates of glucose, organic acids, and the 20 amino acids were determined by time-course analysis of cultured media. Gas chromatography-mass spectrometry analysis of the 13C-labeling of citrate, succinate, fumarate, malate, and aspartate confirmed an isotopically steady state of the cultured cells. After removing the effect of naturally occurring isotopes, the direction of the IDH reaction was determined by computer-aided analysis. The results validated that metabolic engineering methodologies are applicable to soft tissue sarcoma cells derived from p53-null mice, and also demonstrated that reductive glutamine metabolism is active in p53-null soft tissue sarcoma cells under normoxia.

Keywords
Metabolic engineering; Cultured mammalian cell; 13C-tracer experiment; p53; Soft tissue sarcoma; Reductive glutamine metabolism
First Page Preview
Metabolic characterization of cultured mammalian cells by mass balance analysis, tracer labeling experiments and computer-aided simulations
Publisher
Database: Elsevier - ScienceDirect
Journal: Journal of Bioscience and Bioengineering - Volume 120, Issue 6, December 2015, Pages 725–731
Authors
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Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering