Novel strategies for validating metabolic network models using stable isotope tracers
Date
2016
Authors
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Journal ISSN
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Publisher
University of Delaware
Abstract
13C-Metabolic flux analysis (13C-MFA) is a powerful tool for characterizing metabolic networks and flux distributions in living cells. Fluxes provide a quantitative understanding of metabolism that can be applied to metabolic engineering, systems biology, and biomedical research. The accuracy and precision of flux estimates from 13C-MFA are strongly influenced by the design of the 13C labeling experiment. There are three major decision points in designing 13C labeling experiments: (1) experimental layout; (2) 13C tracer selection; and (3) selection of isotopic measurements. Recent advances in these areas have enabled higher quality flux estimates. In this dissertation, we highlight the applicability of these new approaches in validating metabolic network models and estimating metabolic fluxes for several biological systems.
First, we describe an application of parallel labeling experiments for characterizing the metabolism of Clostridium acetobutylicum, an important anaerobe for biofuel production. We present a systematic approach to establish a metabolic model that fit all experimental data from several parallel cultures, providing valuable insights into the metabolism of C. acetobutylicum. Furthermore, we describe the use of 13 C labeling experiments for characterizing the metabolic stress response of C. acetobutylicum to butanol and butyric acid, two industrially-important, but toxic fermentation products.
Second, we describe examples of how 13C amino acid tracers can be used to validate metabolic models and characterize metabolism. The first example tests a common assumption in 13C-MFA, namely that no carbon flows from secondary pathways back to central metabolism. Using multiple 13C amino acid tracers, we determined there is an active metabolic cycle in C. acetobutylicum that runs from aspartate to pyruvate. In the second example, we applied 13C alanine tracers and knockout strains to quantify flux from pyruvate to phosphoenolpyruvate (PEP) in E. coli under gluconeogenic and glycolytic growth. Contrary to current understanding of the PTS, there is a significant in vivo flux from pyruvate to PEP under glycolytic growth.
Lastly, we present a GC-MS based method for measuring glycogen and RNA labeling, and demonstrate the value of these measurements for 13C-MFA in two model biological systems, E. coli and CHO cells. Overall, these measurements improved the precision of 13C-MFA flux estimates.