Metabolic Flux Analysis

¹³C metabolic flux analysis is a collective term to indicate a set of methods to experimentally measure in vivo rates through metabolic pathways and reactions. Since reaction rates are not di per se detectable, stable isotopic tracers are used to infer them form the propagation of ¹³C over time (in dynamic experiments) or from the labeling patterns that emerge when ¹²C and ¹³C fragments are merged in metabolism (in end-point measurements). Mass spectrometry is absolutely instrumental to record the labeling patterns in metabolic intermediates and end-products. In real-life problems (see below) the increased problem complexity calls for denser and more accurate 13C data. Hence, 13C metabolic flux analysis strongly depends on improvements in sensitivity, throughput, and coverage of metabolomics.

General references:

1. Zamboni N, Fendt SM, Rühl M, Sauer U, ¹³C-based metabolic flux analysis, Nat protocols 2009; 4(6):878-892
2. Zamboni N, ¹³C metabolic flux analysis in complex systems, Curr Opin Biotechnol. 2011 Feb;22(1):103-108
3. Zamboni N, Sauer U, Novel biological insights through metabolomics and ¹³C-flux analysis, Curr Opin Microbiol 2009 Oct;12(5):553-8

Methods

Different methods exist with heterogeneous demand of inputs and outputs. In our lab, we applied primarily three approaches: 1. Fluxome profiling Mere statistical analysis of possibly dense 13C-data. Depending on the question, supervised or unsupervised, classification or regression methods can be used. References: Zamboni N, Sauer U, Model-independent fluxome profiling from 2H and 13C experiments for metabolic variant discrimination, Genome Biol. 2004;5(12):R99 Zamboni N and Sauer U, Fluxome profiling in microbes, in Metabolome analyses: strategies for systems biology, S. Vaidyanathan, G.G. Harrigan, and R. Goodacre, Editors. 2005, Springer: New York. p. 307-322

2. Flux ratio analysis Local interpretation of fluxes delivers quantitative information on the relative (%) fluxes of reactions/pathway converging to a common intermediate. Flux ratio analysis requires less information and is amenable to large scale studies, but is difficult to adapt to novel organisms or environmnents. References: Zamboni N, Fendt SM, Rühl M, Sauer U, 13C-based metabolic flux analysis, Nat protocols 2009; 4(6):878-892 Fischer and Sauer, Metabolic flux profiling of Escherichia coli mutants in central carbon metabolism using GC-MS. Eur J Biochem. 2003;270(5):880-91.

3. Isotopomer fitting When comprehensive and quantitative net flux maps are necessary to e.g. derive cell-wide energy or redox balances, we use the 13CFLUX software by the Wiechert group (FZ Jülich, D). This approach is the most demanding in terms of data, time, and complexity.

Current research

Traditional flux analysis methods were developed in the context of metabolic engineering, i.e. for microbial systems and media with single carbon sources. Unfortunately, these systems transfer poorly to more complex conditions
Our current efforts aim at developing new approaches and implement the necessary software to:

• measure fluxes in complex systems
• measure fluxes at high-throughputs
• enable discovery at flux level