Whither metabolic flux analysis in plants?

Daylength variation affects growth, photosynthesis, leaf metabolism, partitioning, and metabolic fluxes

Daylength, a seasonal and latitudinal variable, exerts a substantial impact on plant growth. However, the relationship between daylength and growth is nonproportional, suggesting the existence of adaptive mechanisms. Thus, our study aimed to comprehensively investigate the adaptive strategies employed by plants in response to daylength variation. We grew false flax (Camelina sativa) plants, a model oilseed crop, under long-day (LD) and short-day (SD) conditions and used growth measurements, gas exchange measurements, and isotopic labeling techniques, including 13C, 14C, and 2H2O, to determine responses to different daylengths. Our findings revealed that daylength influences various growth parameters, photosynthetic physiology, carbon partitioning, metabolic fluxes, and metabolite levels. SD plants employed diverse mechanisms to compensate for reduced CO2 fixation in the shorter photoperiod. These mechanisms included enhanced photosynthetic rates and reduced respiration in the light (RL), leading to increased shoot investment. Additionally, SD plants exhibited reduced rates of the glucose 6-phosphate (G6P) shunt and greater partitioning of sugars into starch, thereby sustaining carbon availability during the longer night. Isotopic labeling results further demonstrated substantial alterations in the partitioning of amino acids and TCA cycle intermediates between rapidly and slowly turning over pools. Overall, the results point to multiple developmental, physiological, and metabolic ways in which plants adapt to different daylengths to maintain growth.

A role for fermentation in aerobic conditions as revealed by computational analysis of maize root metabolism during growth by cell elongation

The root is a well-studied example of cell specialisation, yet little is known about the metabolism that supports the transport functions and growth of different root cell types. To address this, we used computational modelling to study metabolism in the elongation zone of a maize lateral root. A functional-structural model captured the cell-anatomical features of the root and modelled how they changed as the root elongated. From these data, we derived constraints for a flux balance analysis model that predicted metabolic fluxes of the 11 concentric rings of cells in the root. We discovered a distinct metabolic flux pattern in the cortical cell rings, endodermis and pericycle (but absent in the epidermis) that involved a high rate of glycolysis and production of the fermentation end-products lactate and ethanol. This aerobic fermentation was confirmed experimentally by metabolite analysis. The use of fermentation in the model was not obligatory but was the most efficient way to meet the specific demands for energy, reducing power and carbon skeletons of expanding cells. Cytosolic acidification was avoided in the fermentative mode due to the substantial consumption of protons by lipid synthesis. These results expand our understanding of fermentative metabolism beyond that of hypoxic niches and suggest that fermentation could play an important role in the metabolism of aerobic tissues.

Cell-type-specific metabolism in plants

Every plant organ contains tens of different cell types, each with a specialized function. These functions are intrinsically associated with specific metabolic flux distributions that permit the synthesis of the ATP, reducing equivalents and biosynthetic precursors demanded by the cell. Investigating such cell-type-specific metabolism is complicated by the mosaic of different cells within each tissue combined with the relative scarcity of certain types. However, techniques for the isolation of specific cells, their analysis in situ by microscopy, or modeling of their function in silico have permitted insight into cell-type-specific metabolism. In this review we present some of the methods used in the analysis of cell-type-specific metabolism before describing what we know about metabolism in several cell types that have been studied in depth; (i) leaf source and sink cells; (ii) glandular trichomes that are capable of rapid synthesis of specialized metabolites; (iii) guard cells that must accumulate large quantities of the osmolytes needed for stomatal opening; (iv) cells of seeds involved in storage of reserves; and (v) the mesophyll and bundle sheath cells of C4 plants that participate in a CO₂ concentrating cycle. Metabolism is discussed in terms of its principal features, connection to cell function and what factors affect the flux distribution. Demand for precursors and energy, availability of substrates and suppression of deleterious processes are identified as key factors in shaping cell-type-specific metabolism.

Combination of long-term 13CO2 labeling and isotopolog profiling allows turnover analysis of photosynthetic pigments in Arabidopsis leaves

BACKGROUND

Living cells maintain and adjust structural and functional integrity by continual synthesis and degradation of metabolites and macromolecules. The maintenance and adjustment of thylakoid membrane involve turnover of photosynthetic pigments along with subunits of protein complexes. Quantifying their turnover is essential to understand the mechanisms of homeostasis and long-term acclimation of photosynthetic apparatus. Here we report methods combining whole-plant long-term ¹³CO₂ labeling and liquid chromatography - mass spectrometry (LC-MS) analysis to determine the size of non-labeled population (NLP) of carotenoids and chlorophylls (Chl) in leaf pigment extracts of partially ¹³C-labeled plants.

RESULTS

The labeling chamber enabled parallel ¹³CO₂ labeling of up to 15 plants of Arabidopsis thaliana with real-time environmental monitoring ([CO₂], light intensity, temperature, relative air humidity and pressure) and recording. No significant difference in growth or photosynthetic pigment composition was found in leaves after 7-d exposure to normal CO₂ (~ 400 ppm) or ¹³CO₂ in the labeling chamber, or in ambient air outside the labeling chamber (control). Following chromatographic separation of the pigments and mass peak assignment by high-resolution Fourier-transform ion cyclotron resonance MS, mass spectra of photosynthetic pigments were analyzed by triple quadrupole MS to calculate NLP. The size of NLP remaining after the 7-d ¹³CO₂ labeling was ~ 10.3% and ~ 11.5% for all-trans- and 9-cis-β-carotene, ~ 21.9% for lutein, ~ 18.8% for Chl a and 33.6% for Chl b, highlighting non-uniform turnover of these pigments in thylakoids. Comparable results were obtained in all replicate plants of the ¹³CO₂ labeling experiment except for three that were showing anthocyanin accumulation and growth impairment due to insufficient water supply (leading to stomatal closure and less ¹³C incorporation).

CONCLUSIONS

Our methods allow ¹³CO₂ labeling and estimation of NLP for photosynthetic pigments with high reproducibility despite potential variations in [¹³CO₂] between the experiments. The results indicate distinct turnover rates of carotenoids and Chls in thylakoid membrane, which can be investigated in the future by time course experiments. Since ¹³C enrichment can be measured in a range of compounds, long-term ¹³CO₂ labeling chamber, in combination with appropriate MS methods, facilitates turnover analysis of various metabolites and macromolecules in plants on a time scale of hours to days.

An automated workflow that generates atom mappings for large-scale metabolic models and its application to Arabidopsis thaliana

Quantification of reaction fluxes of metabolic networks can help us understand how the integration of different metabolic pathways determines cellular functions. Yet, intracellular fluxes cannot be measured directly but are estimated with metabolic flux analysis (MFA), which relies on the patterns of isotope labeling of metabolites in the network. The application of MFA also requires a stoichiometric model with atom mappings that are currently not available for the majority of large-scale metabolic network models, particularly of plants. While automated approaches such as the Reaction Decoder Toolkit (RDT) can produce atom mappings for individual reactions, tracing the flow of individual atoms of the entire reactions across a metabolic model remains challenging. Here we establish an automated workflow to obtain reliable atom mappings for large-scale metabolic models by refining the outcome of RDT, and apply the workflow to metabolic models of Arabidopsis thaliana. We demonstrate the accuracy of RDT through a comparative analysis with atom mappings from a large database of biochemical reactions, MetaCyc. We further show the utility of our automated workflow by simulating ¹⁵ N isotope enrichment and identifying nitrogen (N)-containing metabolites which show enrichment patterns that are informative for flux estimation in future ¹⁵ N-MFA studies of A. thaliana. The automated workflow established in this study can be readily expanded to other species for which metabolic models have been established and the resulting atom mappings will facilitate MFA and graph-theoretic structural analyses with large-scale metabolic networks.

An integrated isotopic labeling and freeze sampling apparatus (ILSA) to support sampling leaf metabolomics at a centi-second scale

BACKGROUND

Photosynthesis close interacts with respiration and nitrogen assimilation, which determine the photosynthetic efficiency of a leaf. Accurately quantifying the metabolic fluxes in photosynthesis, respiration and nitrogen assimilation benefit the design of photosynthetic efficiency improvement. To accurately estimate metabolic fluxes, time-series data including leaf metabolism and isotopic abundance changes should be collected under precisely controlled environments. But for isotopic labelled leaves under defined environments the, time cost of manually sampling usually longer than the turnover time of several intermediates in photosynthetic metabolism. In this case, the metabolic or physiological status of leaf sample would change during the sampling, and the accuracy of metabolomics data could be compromised.

RESULTS

Here we developed an integrated isotopic labeling and freeze sampling apparatus (ILSA), which could finish freeze sampling automatically in 0.05 s. ILSA can not only be used for sampling of photosynthetic metabolism measurement, but also suit for leaf isotopic labeling experiments under controlled environments ([CO₂] and light). Combined with HPLC-MS/MS as the metabolic measurement method, we demonstrated: (1) how pool-size of photosynthetic metabolites change in dark-accumulated rice leaf, and (2) variation in photosynthetic metabolic flux between rice and Arabidopsis thaliana.

CONCLUSIONS

The development of ILSA supports the photosynthetic research on metabolism and metabolic flux analysis and provides a new tool for the study of leaf physiology.

Recent advances in proteomics and metabolomics in plants

Over the past decade, systems biology and plant-omics have increasingly become the main stream in plant biology research. New developments in mass spectrometry and bioinformatics tools, and methodological schema to integrate multi-omics data have leveraged recent advances in proteomics and metabolomics. These progresses are driving a rapid evolution in the field of plant research, greatly facilitating our understanding of the mechanistic aspects of plant metabolisms and the interactions of plants with their external environment. Here, we review the recent progresses in MS-based proteomics and metabolomics tools and workflows with a special focus on their applications to plant biology research using several case studies related to mechanistic understanding of stress response, gene/protein function characterization, metabolic and signaling pathways exploration, and natural product discovery. We also present a projection concerning future perspectives in MS-based proteomics and metabolomics development including their applications to and challenges for system biology. This review is intended to provide readers with an overview of how advanced MS technology, and integrated application of proteomics and metabolomics can be used to advance plant system biology research.

Altering ureide transport in nodulated soybean results in whole-plant adjustments of metabolism, assimilate partitioning, and sink strength

Legumes develop a symbiotic relationship with bacteria that are housed in root nodules and fix atmospheric di-nitrogen (N2) to ammonia. In soybean (Glycine max (L.) Merr.) nodules, the final products of nitrogen (N) fixation are amino acids, and the ureides allantoin and allantoic acid that also serve as the major long-distance N transport forms. Recently, we have shown that increased expression of UPS1 (ureide permease 1) in soybean nodules results in enhanced ureide export from nodules with positive effects on N fixation and seed yield. Here, we demonstrate that changes in the ureide transport processes trigger alterations in allantoin and allantoic acid pools and partitioning throughout the transgenic plants. They further result in adjustments in amino acid availability in, and translocation to, root and shoot sinks. In addition, leaf carbon (C) capture, assimilation and allocation to sinks are improved, accommodating the increased nodule function, and root and shoot growth. Overall, we demonstrate that enhanced ureide partitioning in nodulated soybean leads to a complex rebalancing of N and C acquisition, metabolism, and transport processes with positive consequences for above- and below-ground vegetative biomass, and whole-plant N and C gains.

Validation of carbon isotopologue distribution measurements by GC-MS and application to 13C-metabolic flux analysis of the tricarboxylic acid cycle in Brassica napus leaves

The estimation of metabolic fluxes in photosynthetic organisms represents an important challenge that has gained interest over the last decade with the development of ¹³C-Metabolic Flux Analysis at isotopically non-stationary steady-state. This approach requires a high level of accuracy for the measurement of Carbon Isotopologue Distribution in plant metabolites. But this accuracy has still not been evaluated at the isotopologue level for GC-MS, leading to uncertainties for the metabolic fluxes calculated based on these fragments. Here, we developed a workflow to validate the measurements of CIDs from plant metabolites with GC-MS by producing tailor-made E. coli standard extracts harboring a predictable binomial CID for some organic and amino acids. Overall, most of our TMS-derivatives mass fragments were validated with these standards and at natural isotope abundance in plant matrices. Then, we applied this validated MS method to investigate the light/dark regulation of plant TCA cycle by incorporating U-¹³C-pyruvate to Brassica napus leaf discs. We took advantage of pathway-specific isotopologues/isotopomers observed between two and six hours of labeling to show that the TCA cycle can operate in a cyclic manner under both light and dark conditions. Interestingly, this forward cyclic flux mode has a nearly four-fold higher contribution for pyruvate-to-citrate and pyruvate-to-malate fluxes than the phosphoenolpyruvate carboxylase (PEPc) flux reassimilating carbon derived from some mitochondrial enzymes. The contribution of stored citrate to the mitochondrial TCA cycle activity was also questioned based on dynamics of ¹³C-enrichment in citrate, glutamate and succinate and variations of citrate total amounts under light and dark conditions. Interestingly, there was a light-dependent ¹³C-incorporation into glycine and serine showing that decarboxylations from pyruvate dehydrogenase complex and TCA cycle enzymes were actively reassimilated and could represent up to 5% to net photosynthesis.