Optimal tracers for parallel labeling experiments and 13C metabolic flux analysis: A new precision and synergy scoring system

Abstract

13C-Metabolic flux analysis (13C-MFA) is a widely used approach in metabolic engineering for quantifying intracellular metabolic fluxes. The precision of fluxes determined by 13C-MFA depends largely on the choice of isotopic tracers and the specific set of labeling measurements. A recent advance in the field is the use of parallel labeling experiments for improved flux precision and accuracy. However, as of today, no systemic methods exist for identifying optimal tracers for parallel labeling experiments. In this contribution, we have addressed this problem by introducing a new scoring system and evaluating thousands of different isotopic tracer schemes. Based on this extensive analysis we have identified optimal tracers for 13C-MFA. The best single tracers were doubly 13C-labeled glucose tracers, including [1,6-13C]glucose, [5,6-13C]glucose and [1,2-13C]glucose, which consistently produced the highest flux precision independent of the metabolic flux map (here, 100 random flux maps were evaluated). Moreover, we demonstrate that pure glucose tracers perform better overall than mixtures of glucose tracers. For parallel labeling experiments the optimal isotopic tracers were [1,6-13C]glucose and [1,2-13C]glucose. Combined analysis of [1,6-13C]glucose and [1,2-13C]glucose labeling data improved the flux precision score by nearly 20-fold compared to widely use tracer mixture 80% [1-13C]glucose + 20% [U-13C]glucose.

Comprehensive metabolic modeling of multiple13C-isotopomer data sets to study metabolism in perfused working hearts

“…Because different tracers provide varying degrees of relative flux information (see Fig. 5), the integrated analysis of several tracer experiments can have an additive impact on flux resolution and result in highly precise relative flux estimates (24). The experimental design from Khairallah et al (32) was aptly suited for the application of integrated flux analysis with parallel labeling experiments.…”

“…In studies with multiple animal treatment groups, parallel tracer labeling approaches may not be practical depending on the number of tracers interrogated and the amount of biological replicates required. In efforts to reduce the amount of perfusions required for 13 C-MFA, mixtures of tracers may be the best option for elucidating TCA cycle fluxes in the perfused heart; however, it is likely that this will incur a cost of decreased flux resolution as shown with previous studies (21,24). These aforementioned challenges present interesting questions for the future direction of 13 C-MFA in perfusion studies and warrant further study.…”

“…The ability to improve relative flux parameter estimation through use of multiple 13 Csubstrates relies on the premise that certain substrates can assess different metabolic pathways (23,24). Despite the potential of this technique, no study to date has used comprehensive isotopomer measurements from various tracer perfusions to estimate relative flux parameters.…”

A Pareto approach to resolve the conflict between information gain and experimental costs: Multiple-criteria design of carbon labeling experiments

“…Crown et al identified [3,4- 13 C]- and [2,3,4,5,6- 13 C]-labeled glucose to be favorable for elucidating reaction rates in the oxidative pentose phosphate pathway (PPP) and pyruvate carboxylase flux, respectively, based on a small scale network with two free fluxes [35]. Later on, the same group determined [1,2- 13 C]-, [5,6- 13 C]-, and [1,6- 13 C]-labeled glucose as best single tracers for Escherichia coli wild type [36]. A study of Metallo et al suggested [1,2- 13 C]-labeled glucose to be the optimal commercial tracer for most fluxes in the PPP and glycolysis in lung carcinoma cell lines while uniformly labeled glutamine provided optimal results for tricarboxylic acid cycle (TCA) fluxes [37].…”

Tracing insights into human metabolism using chemical engineering approaches

“…Tracer choice directly impacts the isotopologues and fluxes that can be determined from a particular experiment, and computational approaches have been developed to evaluate, optimize, and design tracer combinations with enhanced resolution [48–50]. For example, combinations of glucose tracers are useful for studying the pentose phosphate pathway [51], and glutamine tracers are particularly informative when studying tricarboxylic acid (TCA) metabolism in proliferating cancer cells [48].…”