Isotopically nonstationary ¹³ C flux analysis of changes in Arabidopsis thaliana leaf metabolism due to high light acclimation

Abstract

Improving plant productivity is an important aim for metabolic engineering. There are few comprehensive methods that quantitatively describe leaf metabolism, although such information would be valuable for increasing photosynthetic capacity, enhancing biomass production, and rerouting carbon flux toward desirable end products. Isotopically nonstationary metabolic flux analysis (INST-MFA) has been previously applied to map carbon fluxes in photoautotrophic bacteria, which involves model-based regression of transient 13 C-labeling patterns of intracellular metabolites. However, experimental and computational difficulties have hindered its application to terrestrial plant systems. We performed in vivo isotopic labeling of Arabidopsis thaliana rosettes with . Approximately 1,400 independent mass isotopomer measurements obtained from analysis of 37 metabolite fragment ions were regressed to estimate 136 total fluxes (54 free fluxes) under each condition. The results provide a comprehensive description of changes in carbon partitioning and overall photosynthetic flux after longterm developmental acclimation of leaves to high light. Despite a doubling in the carboxylation rate, the photorespiratory flux increased from 17 to 28% of net CO 2 assimilation with high-light acclimation (Vc/Vo: 3.5:1 vs. 2.3:1, respectively). This study highlights the potential of 13 C INST-MFA to describe emergent flux phenotypes that respond to environmental conditions or plant physiology and cannot be obtained by other complementary approaches.isotopomer modeling | metabolic flux analysis | photosynthesis | 13 C-labeling | primary metabolism P hotosynthetic organisms assimilate more than 100 billion tons of carbon, ∼15% of the atmospheric total, each year and generate organic compounds for food and renewable chemicals (1). However, photosynthesis is a complex process that responds to heterotrophic tissue demands and environmental stimuli such as drought, temperature, and light intensity (2, 3). The light incident on the plant varies with intensities in the range of 0-2,000 μmol photons·m −2 ·s −1 and can change dramatically because of passing clouds, shading, and the position of the sun. Thus, plants adjust light harvesting and carbon assimilation steps to accommodate many fluctuations, resulting in changes in plant morphology, physiology, and metabolism (4).For 95% of all terrestrial plants (i.e., C3 plants), the reductive pentose phosphate (Calvin-Benson-Bassham, or CBB) cycle directly links light and dark reactions and sustains anabolic activities (5). RuBisCO (ribulose-1,5-bisphosphate carboxylase oxygenase) plays a central role in the cycle by carboxylating ribulose-1,5-bisphosphate (RUBP) with CO 2 to form two 3-phosphoglycerate (3PGA) molecules. The other 10 enzymes in the CBB cycle regenerate the RUBP substrate to repeat this process. RuBisCO has a low turnover rate (∼3/s; ref. 6) and also performs a competitive oxygenation side reaction that limits carboxylation activity. The binding of RuBisCO to oxygen produces 2-phosphoglycolat...

Interactions of C4 Subtype Metabolic Activities and Transport in Maize Are Revealed through the Characterization of DCT2 Mutants

“…13 C labeling was more pronounced in Calvin cycle intermediates, including 3-PGA, ribulose-1,5-bisphosphate, and sedoheptulose-7-phosphate from the wild type relative to dct2-1 (Figure 4) and approached isotopic steady state within 3 min (;85% 13 C). Similar levels of isotope incorporation have been observed in C 3 plants (Ma et al, 2014), though requiring a longer labeling duration (;15 min). By contrast, 13 C enrichment was limited (;20% 13 C) in the dct2-1 line.…”

Regulation of Primary Metabolism in Response to Low Oxygen Availability as Revealed by Carbon and Nitrogen Isotope Redistribution

“…Inhibition of SDH will disrupt the tricarboxylic acid cycle, which leads to a noncyclic reaction pathway that has actually been described earlier to occur in plants and green algae in response to various conditions, including low oxygen availability (Vanlerberghe et al, 1989(Vanlerberghe et al, , 1991Hanning and Heldt, 1993;Schwender et al, 2006;Steuer et al, 2007;Boyle and Morgan, 2009;Tcherkez et al, 2009;Sweetlove et al, 2010;Grafahrend-Belau et al, 2013;Ma et al, 2014). Interestingly, similar observations were made on the relative levels of the metabolites associated with the tricarboxylic acid cycle in antisense SDH tomato (Solanum lycopersicum) plants, which were deficient in the expression of the iron-sulfur subunit of SDH .…”

Inference and prediction of metabolic network fluxes

“…This FBA prediction was recently confirmed in an INST-MFA analysis of Arabidopsis plants acclimated to high light (Ma et al, 2014). The energy-dissipating role of photorespiration has implications for attempts to transfer C 4 photosynthesis to C 3 plants (Hibberd et al, 2008): for the engineered plants to function properly in high light, it will be essential that alternative energydissipating systems have sufficient capacity to replace the role played previously by photorespiration.…”

“…the rate of substrate utilization and the rates of synthesis of biomass components), it is possible to estimate absolute fluxes of the metabolic network under consideration. Recently, the technique has been implemented successfully in Arabidopsis (Arabidopsis thaliana), a technical and computational tour de force that allowed the quantification of 54 fluxes in illuminated leaves labeled with 13 CO 2 (Ma et al, 2014). The availability of specialized software, INCA (Young, 2014) and OpenMeBius (Kajihata et al, 2014), will greatly facilitate the implementation of INST-MFA by automatically generating the system of ordinary differential equations that describes the metabolic network under consideration (defined by the user and including information about the carbon transitions between metabolites) and estimating metabolic fluxes by nonlinear optimization of the parameter fit to the labeling time course of the measured isotopomers.…”