The benefits of being transient: isotope-based metabolic flux analysis at the short time scale

Abstract

Metabolic fluxes are the manifestations of the co-operating actions in a complex network of genes, transcripts, proteins, and metabolites. As a final quantitative endpoint of all cellular interactions, the intracellular fluxes are of immense interest in fundamental as well as applied research. Unlike the quantities of interest in most omics levels, in vivo fluxes are, however, not directly measureable. In the last decade, ¹³C-based metabolic flux analysis emerged as the state-of-the-art technique to infer steady-state fluxes by data from labeling experiments and the use of mathematical models. A very promising new area in systems metabolic engineering research is non-stationary ¹³C-metabolic flux analysis at metabolic steady-state conditions. Several studies have demonstrated an information surplus contained in transient labeling data compared to those taken at the isotopic equilibrium, as it is classically done. Enabled by recent, fairly multi-disciplinary progress, the new method opens several attractive options to (1) generate new insights, e.g., in cellular storage metabolism or the dilution of tracer by endogenous pools and (2) shift limits, inherent in the classical approach, towards enhanced applicability with respect to cultivation conditions and biological systems. We review the new developments in metabolome-based non-stationary ¹³C flux analysis and outline future prospects for accurate in vivo flux measurement.

Non-stationary 13C metabolic flux analysis of Chinese hamster ovary cells in batch culture using extracellular labeling highlights metabolic reversibility and compartmentation

“…As it was shown that reversibility greatly affects labeling dynamics [43], we assumed that the transport reversibility parameter changes in time, even if the net fluxes remain constant. The decrease with time of pyruvate transport reversibility was mechanistically expressed using a hyperbolic function $\mathit{re}{\mathrm{italicv}}_{\mathrm{italicPYR}}=\frac{\mathit{re}{\mathrm{italicv}}_{\mathrm{italicPYR}}^0}{\mathit{time}+\mathit{ϵ}}$, where pyruvate transport reversibility rev PYR decreases from a starting value $\mathit{re}{\mathrm{italicv}}_{\mathrm{italicPYR}}^0$.…”

Tracking the metabolic pulse of plant lipid production with isotopic labeling and flux analyses: Past, present and future

“…3) provide a richer set of data for modeling purposes [321] over steady state analysis alone. Additionally, because the earliest time points are the most sensitive to label provision, they provide a significant amount of information and the experimental duration can be shortened [322,323]. Recent studies have described the incorporation of 13 C into whole plants [324][325][326] and specific photosynthetic tissues, cells or unicellular organisms [66,67,70,327,328].…”

Systems and synthetic biology perspective of the versatile plant-pathogenic and polysaccharide-producing bacterium Xanthomonas campestris

“…In 13 C MFA, metabolites are measured that were labelled with the heavy carbon isotope 13 C [218][219][220][221][222]. The method is useful for resolving metabolic flux when there are two or more pathways in parallel that facilitate metabolic conversions of the same substrate or generate the same product.…”