Flux profiling of photosynthetic carbon metabolism in intact plants

Increased α-ketoglutarate links the C3-C4 intermediate state to C4 photosynthesis in the genus Flaveria

As a complex trait, C4 photosynthesis has multiple independent origins in evolution. Phylogenetic evidence and theoretical analysis suggest that C2 photosynthesis, which is driven by glycine decarboxylation in the bundle sheath cell, may function as a bridge from C3 to C4 photosynthesis. However, the exact molecular mechanism underlying the transition between C2 photosynthesis to C4 photosynthesis remains elusive. Here, we provide evidence suggesting a role of higher α-ketoglutarate (AKG) concentration during this transition. Metabolomic data of 12 Flaveria species, including multiple photosynthetic types, show that AKG concentration initially increased in the C3-C4 intermediate with a further increase in C4 species. Petiole feeding of AKG increases the concentrations of C4-related metabolites in C3-C4 and C4 species but not the activity of C4-related enzymes. Sequence analysis shows that glutamate synthase (Fd-GOGAT), which catalyzes the generation of glutamate using AKG, was under strong positive selection during the evolution of C4 photosynthesis. Simulations with a constraint-based model for C3-C4 intermediate further show that decreasing the activity of Fd-GOGAT facilitated the transition from a C2-dominant to a C4-dominant CO2 concentrating mechanism. All these results provide insight into the mechanistic switch from C3-C4 intermediate to C4 photosynthesis.

The role of metabolomics in informing strategies for improving photosynthesis

Photosynthesis plays a vital role in acclimating to and mitigating climate change, providing food and energy security for a population that is constantly growing, and achieving an economy with zero carbon emissions. A thorough comprehension of the dynamics of photosynthesis, including its molecular regulatory network and limitations, is essential for utilizing it as a tool to boost plant growth, enhance crop yields, and support the production of plant biomass for carbon storage. Photorespiration constrains photosynthetic efficiency and contributes significantly to carbon loss. Therefore, modulating or circumventing photorespiration presents opportunities to enhance photosynthetic efficiency. Over the past eight decades, substantial progress has been made in elucidating the molecular basis of photosynthesis, photorespiration, and the key regulatory mechanisms involved, beginning with the discovery of the canonical Calvin-Benson-Bassham cycle. Advanced chromatographic and mass spectrometric technologies have allowed a comprehensive analysis of the metabolite patterns associated with photosynthesis, contributing to a deeper understanding of its regulation. In this review, we summarize the results of metabolomics studies that shed light on the molecular intricacies of photosynthetic metabolism. We also discuss the methodological requirements essential for effective analysis of photosynthetic metabolism, highlighting the value of this technology in supporting strategies aimed at enhancing photosynthesis.

Stable Isotope Labeling and Quantification of Photosynthetic Metabolites

Stable isotope labeling with 13CO2 coupled with mass spectrometry allows monitoring the incorporation of 13C into photosynthetic intermediates and is a powerful technique for the investigation of the metabolic dynamics of photosynthesis. We describe here a protocol for 13CO2 labeling of large leaved plants and of Arabidopsis thaliana rosette, and a method for quantitative mass spectrometry analyses to uncover the labeling pattern of Calvin-Benson cycle sucrose, and starch synthesis as well as carbon-concentrating mechanism metabolites.

13CO2-labelling and Sampling in Algae for Flux Analysis of Photosynthetic and Central Carbon Metabolism

The flux in photosynthesis can be studied by performing 13CO2 pulse labelling and analysing the temporal labelling kinetics of metabolic intermediates using gas or liquid chromatography linked to mass spectrometry. Metabolic flux analysis (MFA) is the primary approach for analysing metabolic network function and quantifying intracellular metabolic fluxes. Different MFA approaches differ based on the metabolic state (steady vs. non-steady state) and the use of stable isotope tracers. The main methodology used to investigate metabolic systems is metabolite steady state associated with stable isotope labelling experiments. Specifically, in biological systems like photoautotrophic organisms, isotopic non-stationary 113C metabolic flux analysis at metabolic steady state with transient isotopic labelling (13C-INST-MFA) is required. The common requirement for metabolic steady state, alongside its very short half-timed reactions, complicates robust MFA of photosynthetic metabolism. While custom gas chambers design has addressed these challenges in various model plants, no similar tools were developed for liquid photosynthetic cultures (e.g., algae, cyanobacteria), where diffusion and equilibration of inorganic carbon species in the medium entails a new dimension of complexity. Recently, a novel tailor-made microfluidics labelling system has been introduced, supplying short 13CO2 pulses at steady state, and resolving fluxes across most photosynthetic metabolic pathways in algae. The system involves injecting algal cultures and medium containing pre-equilibrated inorganic 13C into a microfluidic mixer, followed by rapid metabolic quenching, enabling precise seconds-level label pulses. This was complemented by a 13CO2-bubbling-based open labelling system (photobioreactor), allowing long pulses (minutes-hours) required for investigating fluxes into central C metabolism and major products. This combined labelling procedure provides a comprehensive fluxome cover for most algal photosynthetic and central C metabolism pathways, thus allowing comparative flux analyses across algae and plants.

Evolution of gene regulatory network of C4 photosynthesis in the genus Flaveria reveals the evolutionary status of C3-C4 intermediate species

C₄ photosynthesis evolved from ancestral C₃ photosynthesis by recruiting pre-existing genes to fulfill new functions. The enzymes and transporters required for the C₄ metabolic pathway have been intensively studied and well documented; however, the transcription factors (TFs) that regulate these C₄ metabolic genes are not yet well understood. In particular, how the TF regulatory network of C₄ metabolic genes was rewired during the evolutionary process is unclear. Here, we constructed gene regulatory networks (GRNs) for four closely evolutionarily related species from the genus Flaveria, which represent four different evolutionary stages of C₄ photosynthesis: C₃ (F. robusta), type I C₃-C₄ (F. sonorensis), type II C₃-C₄ (F. ramosissima), and C₄ (F. trinervia). Our results show that more than half of the co-regulatory relationships between TFs and core C₄ metabolic genes are species specific. The counterparts of the C₄ genes in C₃ species were already co-regulated with photosynthesis-related genes, whereas the required TFs for C₄ photosynthesis were recruited later. The TFs involved in C₄ photosynthesis were widely recruited in the type I C₃-C₄ species; nevertheless, type II C₃-C₄ species showed a divergent GRN from C₄ species. In line with these findings, a ¹³CO₂ pulse-labeling experiment showed that the CO₂ initially fixed into C₄ acid was not directly released to the Calvin-Benson-Bassham cycle in the type II C₃-C₄ species. Therefore, our study uncovered dynamic changes in C₄ genes and TF co-regulation during the evolutionary process; furthermore, we showed that the metabolic pathway of the type II C₃-C₄ species F. ramosissima represents an alternative evolutionary solution to the ammonia imbalance in C₃-C₄ intermediate species.

13C metabolic flux analysis: Classification and characterization from the perspective of mathematical modeling and application in physiological research of neural cell

¹³C metabolic flux analysis (¹³C-MFA) has emerged as a forceful tool for quantifying in vivo metabolic pathway activity of different biological systems. This technology plays an important role in understanding intracellular metabolism and revealing patho-physiology mechanism. Recently, it has evolved into a method family with great diversity in experiments, analytics, and mathematics. In this review, we classify and characterize the various branch of ¹³C-MFA from a unified perspective of mathematical modeling. By linking different parts in the model to each step of its workflow, the specific technologies of ¹³C-MFA are put into discussion, including the isotope labeling model (ILM), isotope pattern measuring technique, optimization algorithm and statistical method. Its application in physiological research in neural cell has also been reviewed.

Rising rates of starch degradation during daytime and trehalose 6-phosphate optimize carbon availability

Many plants, including Arabidopsis (Arabidopsis thaliana), accumulate starch in the light and remobilize it to support maintenance and growth at night. Starch synthesis and degradation are usually viewed as temporally separate processes. Recently, we reported that starch is also degraded in the light. Degradation rates are generally low early in the day but rise with time. Here, we show that the rate of degradation in the light depends on time relative to dawn rather than dusk. We also show that degradation in the light is inhibited by trehalose 6-phosphate, a signal for sucrose availability. The observed responses of degradation in the light can be simulated by a skeletal model in which the rate of degradation is a function of starch content divided by time remaining until dawn. The fit is improved by extension to include feedback inhibition of starch degradation by trehalose 6-phosphate. We also investigate possible functions of simultaneous starch synthesis and degradation in the light, using empirically parameterized models and experimental approaches. The idea that this cycle buffers growth against falling rates of photosynthesis at twilight is supported by data showing that rates of protein and cell wall synthesis remain high during a simulated dusk twilight. Degradation of starch in the light may also counter over-accumulation of starch in long photoperiods and stabilize signaling around dusk. We conclude that starch degradation in the light is regulated by mechanisms similar to those that operate at night and is important for stabilizing carbon availability and signaling, thus optimizing growth in natural light conditions.

An Arabidopsis GCMS chemical ionization technique to quantify adaptive responses in central metabolism

We present a methodology to survey central metabolism in 13CO2-labeled Arabidopsis (Arabidopsis thaliana) rosettes by ammonia positive chemical ionization-gas chromatography-mass spectrometry. This technique preserves the molecular ion cluster of methyloxime/trimethylsilyl-derivatized analytes up to 1 kDa, providing unambiguous nominal mass assignment of >200 central metabolites and 13C incorporation rates into a subset of 111 from the tricarboxylic acid (TCA) cycle, photorespiratory pathway, amino acid metabolism, shikimate pathway, and lipid and sugar metabolism. In short-term labeling assays, we observed plateau labeling of ∼35% for intermediates of the photorespiratory cycle except for glyoxylate, which reached only ∼4% labeling and was also present at molar concentrations several fold lower than other photorespiratory intermediates. This suggests photorespiratory flux may involve alternate intermediate pools besides the generally accepted route through glyoxylate. Untargeted scans showed that in illuminated leaves, noncyclic TCA cycle flux and citrate export to the cytosol revert to a cyclic flux mode following methyl jasmonate (MJ) treatment. MJ also caused a block in the photorespiratory transamination of glyoxylate to glycine. Salicylic acid treatment induced the opposite effects in both cases, indicating the antagonistic relationship of these defense signaling hormones is preserved at the metabolome level. We provide complete chemical ionization spectra for 203 Arabidopsis metabolites from central metabolism, which uniformly feature the unfragmented pseudomolecular ion as the base peak. This unbiased, soft ionization technique is a powerful screening tool to identify adaptive metabolic trends in photosynthetic tissue and represents an important advance in methodology to measure plant metabolic flux.

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.

Point mutations that boost aromatic amino acid production and CO2 assimilation in plants

Aromatic compounds having unusual stability provide high-value chemicals and considerable promise for carbon storage. Terrestrial plants can convert atmospheric CO₂ into diverse and abundant aromatic compounds. However, it is unclear how plants control the shikimate pathway that connects the photosynthetic carbon fixation with the biosynthesis of aromatic amino acids, the major precursors of plant aromatic natural products. This study identified suppressor of tyra2 (sota) mutations that deregulate the first step in the plant shikimate pathway by alleviating multiple effector-mediated feedback regulation in Arabidopsis thaliana. The sota mutant plants showed hyperaccumulation of aromatic amino acids accompanied by up to a 30% increase in net CO₂ assimilation. The identified mutations can be used to enhance plant-based, sustainable conversion of atmospheric CO₂ to high-energy and high-value aromatic compounds.

An efficient LC-MS method for isomer separation and detection of sugars, phosphorylated sugars, and organic acids

Assessing central carbon metabolism in plants can be challenging due to the dynamic range in pool sizes, with low levels of important phosphorylated sugars relative to more abundant sugars and organic acids. Here, we report a sensitive liquid chromatography-mass spectrometry method for analysing central metabolites on a hybrid column, where both anion-exchange and hydrophilic interaction chromatography (HILIC) ligands are embedded in the stationary phase. The liquid chromatography method was developed for enhanced selectivity of 27 central metabolites in a single run with sensitivity at femtomole levels observed for most phosphorylated sugars. The method resolved phosphorylated hexose, pentose, and triose isomers that are otherwise challenging. Compared with a standard HILIC approach, these metabolites had improved peak areas using our approach due to ion enhancement or low ion suppression in the biological sample matrix. The approach was applied to investigate metabolism in high lipid-producing tobacco leaves that exhibited increased levels of acetyl-CoA, a precursor for oil biosynthesis. The application of the method to isotopologue detection and quantification was considered through evaluating 13C-labeled seeds from Camelina sativa. The method provides a means to analyse intermediates more comprehensively in central metabolism of plant tissues.

Design and fabrication of an improved dynamic flow cuvette for 13CO2 labeling in Arabidopsis plants

BACKGROUND

Stable isotope labeling is a non-invasive, sensitive means of monitoring metabolic flux in plants. The most physiologically meaningful information is obtained from experiments that take advantage of the natural photosynthetic carbon assimilation pathway to introduce a traceable marker with minimal effects on the physiology of the organism. The fundamental substrate in isotopic labeling experiments is ¹³CO₂, which can reveal the earliest events in carbon assimilation and realistically portray downstream metabolism when administered under conditions suitable for making kinetic inferences. Efforts to improve the accuracy and resolution of whole plant labeling techniques have focused on improvements in environmental control, air flow characteristics, and harvesting methods.

RESULTS

Here we present a dynamic flow cuvette designed for single Arabidopsis thaliana labeling experiments. We have also verified its suitability for labeling Nicotiana benthamiana and essential oils in Pelargonium graveolens. Complete plans for fabrication of this device are included. The design includes three important innovations. First, uniform, circular air flow over the rosette surface is accomplished by a fan and deflector that creates a mini-cyclone effect within the chamber interior. Second, a network of circulating canals connected to a water bath provides temperature control to within ± 0.1 ºC under variable irradiance, humidity, and air flow conditions. When photosynthetically active radiation (PAR) was varied over a range of 1000 μEinsteins m^-2 s^-1 with no adjustment to the external temperature control system, the abaxial leaf temperature changed by < 3 ºC/1000 PAR. Third, the device is fully compatible with liquid nitrogen quenching of metabolic activity without perturbation of the light environment. For short labeling experiments (< 10 s), the most critical variable is the half-life (t_1/2) of the atmosphere within the chamber, which determines the maximum resolution of the labeling system. Using an infrared gas analyzer, we monitored the atmospheric half-life during the transition from ¹²CO₂ to ¹³CO₂ air at different flow rates and determined that 3.5 L min^-1 is the optimal flow rate to initiate labeling (t_1/2 ~ 5 s). Under these conditions, we observed linear incorporation of ¹³C into triose phosphate with labeling times as short as 5 s.

CONCLUSIONS

Advances in our ability to conduct short term labeling experiments are critical to understanding of the rates and control of the earliest steps in plant metabolism. Precise kinetic measurements in whole plants using ¹³CO₂ inform metabolic models and reveal control points that can be exploited in agricultural or biotechnological contexts. The dynamic labeling cuvette presented here is suitable for studying early events in carbon assimilation and provides high resolution kinetic data for studies of metabolism in intact plants under physiologically realistic scenarios.

Pool size measurements improve precision of flux estimates but increase sensitivity to unmodeled reactions outside the core network in isotopically nonstationary metabolic flux analysis (INST-MFA)

Metabolic flux analysis (MFA) involves model-based estimation of metabolic reaction rates (i.e., fluxes) and, in some cases, metabolite content (i.e., pool sizes) from experimental measurements. Applying MFA to biological data helps determine the fate of substrates and the activity of specific pathways within metabolic networks. However, reliably estimating fluxes by using simplified "core" models to predict the dynamics of larger metabolic networks remains a challenge. One point of uncertainty relates to the advantages and potential pitfalls of including pool size measurements as experimental inputs for isotopically nonstationary MFA (INST-MFA). Here, we directly assessed the role of pool sizes using various core models and simulated datasets. To investigate the effects of pool size measurements on INST-MFA, we assessed the accuracy and precision of flux estimates obtained using different subsets of data (e.g., with or without pool size measurements) and simple network models that either matched or differed from the true network. The inclusion of pool size measurements provided incremental improvements to the precision of the flux estimates. However, adding pool size measurements increased the sensitivity of the flux solution to unmodeled reactions outside the core network. These results were confirmed using a large E. coli model that is representative of realistic metabolic networks examined in MFA studies. Our findings indicate that accurate flux estimates can be obtained in the absence of pool size measurements, even when using core models that lack full network coverage. Addition of pool size measurements to INST-MFA datasets may reveal the activity of non-core reactions that influence the labeling dynamics and therefore necessitate network expansion in order to reconcile all available data to the model. Our findings also emphasize the key role that goodness-of-fit testing plays in assessing the quality of model fits obtained with INST-MFA. This article is protected by copyright. All rights reserved.

Carbon flux through photosynthesis and central carbon metabolism show distinct patterns between algae, C3 and C4 plants

Photosynthesis-related pathways are regarded as a promising avenue for crop improvement. Whilst empirical studies have shown that photosynthetic efficiency is higher in microalgae than in C3 or C4 crops, the underlying reasons remain unclear. Using a tailor-made microfluidics labelling system to supply 13CO2 at steady state, we investigated in vivo labelling kinetics in intermediates of the Calvin Benson cycle and sugar, starch, organic acid and amino acid synthesis pathways, and in protein and lipids, in Chlamydomonas reinhardtii, Chlorella sorokiniana and Chlorella ohadii, which is the fastest growing green alga on record. We estimated flux patterns in these algae and compared them with published and new data from C3 and C4 plants. Our analyses identify distinct flux patterns supporting faster growth in photosynthetic cells, with some of the algae exhibiting faster ribulose 1,5-bisphosphate regeneration and increased fluxes through the lower glycolysis and anaplerotic pathways towards the tricarboxylic acid cycle, amino acid synthesis and lipid synthesis than in higher plants.

Assessing Protein Synthesis and Degradation Rates in Arabidopsis thaliana Using Amino Acid Analysis

Plants continually synthesize and degrade proteins, for example, to adjust protein content during development or during adaptation to new environments. In order to estimate global protein synthesis and degradation rates in plants, we developed a relatively simple and inexpensive method using a combination of ¹³ CO₂ labeling and mass spectrometry-based analyses. Arabidopsis thaliana plants are subjected to a 24-hr ¹³ CO₂ pulse followed by a 4-day ¹² CO₂ chase. Soluble alanine and serine from total protein and glucose from cell wall material are analyzed by gas chromatography time-of-flight mass spectrometry (GC-TOF-MS) and their ¹³ C enrichment (%) is estimated. The rate of protein synthesis during the ¹³ CO₂ pulse experiment is defined as the rate of incorporation of labeled amino acids into proteins normalized by a correction factor for incomplete enrichment in free amino acid pools. The rate of protein degradation is estimated as the difference between the rate of protein synthesis and the relative growth rate calculated using the ¹³ C enrichment of glucose from cell wall material. Degradation rates are also estimated from the ¹² CO₂ pulse experiment. The following method description includes setting up and performing labeling experiments, preparation and measurement of samples, and calculation steps. In addition, an R script is provided for the calculations. 2021 The Authors. Current Protocols published by Wiley Periodicals LLC. Basic Protocol 1: Setting up the ¹³ CO₂ labeling system and stable isotope labeling of Arabidopsis thaliana rosette leaves Basic Protocol 2: Extraction of soluble amino acids for GC-TOF-MS analysis Basic Protocol 3: Preparation of amino acids from total protein for GC-TOF-MS analysis Basic Protocol 4: Preparation of sugars from cell wall material for GC-TOF-MS analysis Basis Protocol 5: GC-TOF-MS analysis of ¹³ C-labeled samples and estimation of ¹³ C enrichment (%) Basis Protocol 6: Estimation of protein synthesis and degradation rates.

Photorespiration: The Futile Cycle?

Photorespiration, or C₂ photosynthesis, is generally considered a futile cycle that potentially decreases photosynthetic carbon fixation by more than 25%. Nonetheless, many essential processes, such as nitrogen assimilation, C₁ metabolism, and sulfur assimilation, depend on photorespiration. Most studies of photosynthetic and photorespiratory reactions are conducted with magnesium as the sole metal cofactor despite many of the enzymes involved in these reactions readily associating with manganese. Indeed, when manganese is present, the energy efficiency of these reactions may improve. This review summarizes some commonly used methods to quantify photorespiration, outlines the influence of metal cofactors on photorespiratory enzymes, and discusses why photorespiration may not be as wasteful as previously believed.

Recent Advances in Carbon and Nitrogen Metabolism in C3 Plants

C and N are the most important essential elements constituting organic compounds in plants. The shoots and roots depend on each other by exchanging C and N through the xylem and phloem transport systems. Complex mechanisms regulate C and N metabolism to optimize plant growth, agricultural crop production, and maintenance of the agroecosystem. In this paper, we cover the recent advances in understanding C and N metabolism, regulation, and transport in plants, as well as their underlying molecular mechanisms. Special emphasis is given to the mechanisms of starch metabolism in plastids and the changes in responses to environmental stress that were previously overlooked, since these changes provide an essential store of C that fuels plant metabolism and growth. We present general insights into the system biology approaches that have expanded our understanding of core biological questions related to C and N metabolism. Finally, this review synthesizes recent advances in our understanding of the trade-off concept that links C and N status to the plant's response to microorganisms.

Enzymes as Parts in Need of Replacement - and How to Extend Their Working Life

Enzymes catalyze reactions in vivo at different rates and each enzyme molecule has a lifetime limit before it is degraded and replaced to enable catalysis to continue. Considering these rates together as a unitless ratio of catalytic cycles until replacement (CCR) provides a new quantitative tool to assess the replacement schedule of and energy investment into enzymes as they relate to function. Here, we outline the challenges of determining CCRs and new approaches to overcome them and then assess the CCRs of selected enzymes in bacteria and plants to reveal a range of seven orders of magnitude for this ratio. Modifying CCRs in plants holds promise to lower cellular costs, to tailor enzymes for particular environments, and to breed enzyme improvements for crop productivity.

Modeling Plant Metabolism: From Network Reconstruction to Mechanistic Models

Mathematical modeling of plant metabolism enables the plant science community to understand the organization of plant metabolism, obtain quantitative insights into metabolic functions, and derive engineering strategies for manipulation of metabolism. Among the various modeling approaches, metabolic pathway analysis can dissect the basic functional modes of subsections of core metabolism, such as photorespiration, and reveal how classical definitions of metabolic pathways have overlapping functionality. In the many studies using constraint-based modeling in plants, numerous computational tools are currently available to analyze large-scale and genome-scale metabolic networks. For ¹³C-metabolic flux analysis, principles of isotopic steady state have been used to study heterotrophic plant tissues, while nonstationary isotope labeling approaches are amenable to the study of photoautotrophic and secondary metabolism. Enzyme kinetic models explore pathways in mechanistic detail, and we discuss different approaches to determine or estimate kinetic parameters. In this review, we describe recent advances and challenges in modeling plant metabolism.

Carotenoid Isotopolog Profiling in 13C-Labeled Leaf Extracts by LC-MS and LC-FTICR-MS

Mass spectrometry (MS)-based metabolite analysis combined with stable isotope labeling offers a powerful tool to study dynamic regulation of metabolic pathways and metabolite fluxes in biological systems. Here we describe a method to analyze the composition of carotenoid isotopologs in ¹³C-labeled leaf extracts by using liquid chromatography (LC)-MS and LC-Fourier transform ion cyclotron resonance (FTICR)-MS. High mass resolution of the latter enables unambiguous assignment of observed mass to a unique chemical formula. Based on peak intensity the relative abundance and the degree of ¹³C labeling are calculated for individual carotenoid isotopologs.

Evolution and regulation of nitrogen flux through compartmentalized metabolic networks in a marine diatom

Diatoms outcompete other phytoplankton for nitrate, yet little is known about the mechanisms underpinning this ability. Genomes and genome-enabled studies have shown that diatoms possess unique features of nitrogen metabolism however, the implications for nutrient utilization and growth are poorly understood. Using a combination of transcriptomics, proteomics, metabolomics, fluxomics, and flux balance analysis to examine short-term shifts in nitrogen utilization in the model pennate diatom in Phaeodactylum tricornutum, we obtained a systems-level understanding of assimilation and intracellular distribution of nitrogen. Chloroplasts and mitochondria are energetically integrated at the critical intersection of carbon and nitrogen metabolism in diatoms. Pathways involved in this integration are organelle-localized GS-GOGAT cycles, aspartate and alanine systems for amino moiety exchange, and a split-organelle arginine biosynthesis pathway that clarifies the role of the diatom urea cycle. This unique configuration allows diatoms to efficiently adjust to changing nitrogen status, conferring an ecological advantage over other phytoplankton taxa.

Here, using the diatom Phaeodactylum tricornutum as a model organism, the authors combine functional genomics, phylogenetics, and metabolic modeling to describe how diatoms might have functionally integrated nitrogen metabolism during evolution and how metabolic flux is regulated across cellular compartments

Advances in metabolic flux analysis toward genome-scale profiling of higher organisms

Methodological and technological advances have recently paved the way for metabolic flux profiling in higher organisms, like plants. However, in comparison with omics technologies, flux profiling has yet to provide comprehensive differential flux maps at a genome-scale and in different cell types, tissues, and organs. Here we highlight the recent advances in technologies to gather metabolic labeling patterns and flux profiling approaches. We provide an opinion of how recent local flux profiling approaches can be used in conjunction with the constraint-based modeling framework to arrive at genome-scale flux maps. In addition, we point at approaches which use metabolomics data without introduction of label to predict either non-steady state fluxes in a time-series experiment or flux changes in different experimental scenarios. The combination of these developments allows an experimentally feasible approach for flux-based large-scale systems biology studies.

The Importance of Experimental Design, Quality Assurance, and Control in Plant Metabolomics Experiments

The output of metabolomics relies to a great extent upon the methods and instrumentation to identify, quantify, and access spatial information on as many metabolites as possible. However, the most modern machines and sophisticated tools for data analysis cannot compensate for inappropriate harvesting and/or sample preparation procedures that modify metabolic composition and can lead to erroneous interpretation of results. In addition, plant metabolism has a remarkable degree of complexity, and the number of identified compounds easily surpasses the number of samples in metabolomics analyses, increasing false discovery risk. These aspects pose a large challenge when carrying out plant metabolomics experiments. In this chapter, we address the importance of a proper experimental design taking into consideration preventable complications and unavoidable factors to achieve success in metabolomics analysis. We also focus on quality control and standardized procedures during the metabolomics workflow.

Carbon Atomic Survey for Identification of Selected Metabolic Fluxes

Stable-isotope-labeling experiments have become a frequently used tool to investigate different metabolic systems. They have been recently applied to several comprehensive studies in plant metabolomics providing interesting insights into metabolic dynamics and regulation. However, the complexity of mass spectrometry data originating from such experiments is rarely fully explored. Data analysis often considers metabolites in their entirety which obscures important information at the atomic level. Recently, the use of mass spectrometry fragmentation for obtaining positional-labeling information was described for a few specific metabolites. Here, we describe a general methodology that can be applied for extracting positional-labeling information based on the characterization of fragments that are inherent in gas chromatography electron impact mass spectrometry (GC-EI-MS) chromatograms.

Gas Chromatography-Mass Spectrometry-Based 13C-Labeling Studies in Plant Metabolomics

Stable-isotope labeling analysis has been used to discover new metabolic pathways and their key regulatory points in a wide range of organisms. Given the complexity of the plant metabolic network, this analysis provides information complementary to that obtained from metabolite profiling that can be used to understand how plants cope with adverse conditions, and how metabolism varies between different cells, tissues, and organs. Here we describe the experimental procedures from sample harvesting and extraction to mass spectral analysis and interpretation that allow the researcher to perform ¹³C-labeling experiments. A wide range of plant material, from single cells to whole plants, can be used to investigate the metabolic fate of the ¹³C from a predefined tracer. Thus, a key point of this analysis is to choose the correct biological system, the substrate and the condition to be investigated; all of which implicitly relies on the biological question to be investigated. Rapid sample quenching and a careful data analysis are also critical points in such studies. By contrast to other metabolomic approaches, stable-isotope labeling can provide information concerning the fluxes through metabolic networks, which is essential for understanding and manipulating metabolic phenotypes and therefore of pivotal importance for both systems biology and plant metabolic engineering.

Quantification of Photorespiratory Intermediates by Mass Spectrometry-Based Approaches

Photorespiration is an essential metabolic process in plants occurring via the oxygenase reaction of RuBisCO. In order to understand this process, it is essential to determine the amounts of intermediates involved. For this purpose we combined mass spectrometry-based approaches and the use of authentic standards for the quantification of photorespiratory intermediates. Here we describe protocols for the extraction and quantification of 2-phosphoglycolate (2PG) by LC-MS/MS and serine, glycine, glycolate, hydroxypyruvate, glyoxylate, and glycerate by GC-MS.

iReMet-flux: constraint-based approach for integrating relative metabolite levels into a stoichiometric metabolic models

MOTIVATION

Understanding the rerouting of metabolic reaction fluxes upon perturbations has the potential to link changes in molecular state of a cellular system to alteration of growth. Yet, differential flux profiling on a genome-scale level remains one of the biggest challenges in systems biology. This is particularly relevant in plants, for which fluxes in autotrophic growth necessitate time-consuming instationary labeling experiments and costly computations, feasible for small-scale networks.

RESULTS

Here we present a computationally and experimentally facile approach, termed iReMet-Flux, which integrates relative metabolomics data in a metabolic model to predict differential fluxes at a genome-scale level. Our approach and its variants complement the flux estimation methods based on radioactive tracer labeling. We employ iReMet-Flux with publically available metabolic profiles to predict reactions and pathways with altered fluxes in photo-autotrophically grown Arabidopsis and four photorespiratory mutants undergoing high-to-low CO2 acclimation. We also provide predictions about reactions and pathways which are most strongly regulated in the investigated experiments. The robustness and variability analyses, tailored to the formulation of iReMet-Flux, demonstrate that the findings provide biologically relevant information that is validated with external measurements of net CO2 exchange and biomass production. Therefore, iReMet-Flux paves the wave for mechanistic dissection of the interplay between pathways of primary and secondary metabolisms at a genome-scale.

AVAILABILITY AND IMPLEMENTATION

The source code is available from the authors upon request.

CONTACT

nikoloski@mpimp-golm.mpg.de

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Fluxomics links cellular functional analyses to whole-plant phenotyping

Fluxes through metabolic pathways reflect the integration of genetic and metabolic regulations. While it is attractive to measure all the mRNAs (transcriptome), all the proteins (proteome), and a large number of the metabolites (metabolome) in a given cellular system, linking and integrating this information remains difficult. Measurement of metabolome-wide fluxes (termed the fluxome) provides an integrated functional output of the cell machinery and a better tool to link functional analyses to plant phenotyping. This review presents and discusses sets of methodologies that have been developed to measure the fluxome. First, the principles of metabolic flux analysis (MFA), its 'short time interval' version Inst-MFA, and of constraints-based methods, such as flux balance analysis and kinetic analysis, are briefly described. The use of these powerful methods for flux characterization at the cellular scale up to the organ (fruits, seeds) and whole-plant level is illustrated. The added value given by fluxomics methods for unravelling how the abiotic environment affects flux, the process, and key metabolic steps are also described. Challenges associated with the development of fluxomics and its integration with 'omics' for thorough plant and organ functional phenotyping are discussed. Taken together, these will ultimately provide crucial clues for identifying appropriate target plant phenotypes for breeding.

13CO2 Labeling and Mass Spectral Analysis of Photorespiration

Photorespiratory metabolism is compartmented over the chloroplast, peroxisome, cytosol, and mitochondria, and due to its complex structure it is often the case that metabolite levels alone are not able to fully describe photorespiration. Metabolic fluxes represent a more meaningful biological description of metabolism, adding to metabolite levels and often revealing different aspects of the system such as the presence of inactive metabolic pools of photorespiratory intermediates. We describe here a protocol for the ¹³CO₂ feeding of Arabidopsis and tracing of ¹³C enriched metabolites for metabolic fluxes estimation, which allows high throughput analysis of labeling pattern on different metabolites involved in photorespiration and downstream processes.

Metabolite pools and carbon flow during C4 photosynthesis in maize: 13CO2 labeling kinetics and cell type fractionation

Worldwide efforts to engineer C4 photosynthesis into C3 crops require a deep understanding of how this complex pathway operates. CO2 is incorporated into four-carbon metabolites in the mesophyll, which move to the bundle sheath where they are decarboxylated to concentrate CO2 around RuBisCO. We performed dynamic 13CO2 labeling in maize to analyze C flow in C4 photosynthesis. The overall labeling kinetics reflected the topology of C4 photosynthesis. Analyses of cell-specific labeling patterns after fractionation to enrich bundle sheath and mesophyll cells revealed concentration gradients to drive intercellular diffusion of malate, but not pyruvate, in the major CO2-concentrating shuttle. They also revealed intercellular concentration gradients of aspartate, alanine, and phosphenolpyruvate to drive a second phosphoenolpyruvate carboxykinase (PEPCK)-type shuttle, which carries 10-14% of the carbon into the bundle sheath. Gradients also exist to drive intercellular exchange of 3-phosphoglycerate and triose-phosphate. There is rapid carbon exchange between the Calvin-Benson cycle and the CO2-concentrating shuttle, equivalent to ~10% of carbon gain. In contrast, very little C leaks from the large pools of metabolites in the C concentration shuttle into respiratory metabolism. We postulate that the presence of multiple shuttles, alongside carbon transfer between them and the Calvin-Benson cycle, confers great flexibility in C4 photosynthesis.

Can stable isotope mass spectrometry replace ‎radiolabelled approaches in metabolic studies?

Metabolic pathways and the key regulatory points thereof can be deduced using isotopically labelled substrates. One prerequisite is the accurate measurement of the labeling pattern of targeted metabolites. The subsequent estimation of metabolic fluxes following incubation in radiolabelled substrates has been extensively used. Radiolabelling is a sensitive approach and allows determination of total label uptake since the total radiolabel content is easy to detect. However, the incubation of cells, tissues or the whole plant in a stable isotope enriched environment and the use of either mass spectrometry or nuclear magnetic resonance techniques to determine label incorporation within specific metabolites offers the possibility to readily obtain metabolic information with higher resolution. It additionally also offers an important complement to other post-genomic strategies such as metabolite profiling providing insights into the regulation of the metabolic network and thus allowing a more thorough description of plant cellular function. Thus, although safety concerns mean that stable isotope feeding is generally preferred, the techniques are in truth highly complementary and application of both approaches in tandem currently probably provides the best route towards a comprehensive understanding of plant cellular metabolism.

Plants in silico: why, why now and what?--an integrative platform for plant systems biology research

A paradigm shift is needed and timely in moving plant modelling from largely isolated efforts to a connected community endeavour that can take full advantage of advances in computer science and in mechanistic understanding of plant processes. Plants in silico (Psi) envisions a digital representation of layered dynamic modules, linking from gene networks and metabolic pathways through to cellular organization, tissue, organ and whole plant development, together with resource capture and use efficiency in dynamic competitive environments, ultimately allowing a mechanistically rich simulation of the plant or of a community of plants in silico. The concept is to integrate models or modules from different layers of organization spanning from genome to phenome to ecosystem in a modular framework allowing the use of modules of varying mechanistic detail representing the same biological process. Developments in high-performance computing, functional knowledge of plants, the internet and open-source version controlled software make achieving the concept realistic. Open source will enhance collaboration and move towards testing and consensus on quantitative theoretical frameworks. Importantly, Psi provides a quantitative knowledge framework where the implications of a discovery at one level, for example, single gene function or developmental response, can be examined at the whole plant or even crop and natural ecosystem levels.

Reduced mitochondrial malate dehydrogenase activity has a strong effect on photorespiratory metabolism as revealed by 13C labelling

Mitochondrial malate dehydrogenase (mMDH) catalyses the interconversion of malate and oxaloacetate (OAA) in the tricarboxylic acid (TCA) cycle. Its activity is important for redox control of the mitochondrial matrix, through which it may participate in regulation of TCA cycle turnover. In Arabidopsis, there are two isoforms of mMDH. Here, we investigated to which extent the lack of the major isoform, mMDH1 accounting for about 60% of the activity, affected leaf metabolism. In air, rosettes of mmdh1 plants were only slightly smaller than wild type plants although the fresh weight was decreased by about 50%. In low CO2 the difference was much bigger, with mutant plants accumulating only 14% of fresh weight as compared to wild type. To investigate the metabolic background to the differences in growth, we developed a (13)CO2 labelling method, using a custom-built chamber that enabled simultaneous treatment of sets of plants under controlled conditions. The metabolic profiles were analysed by gas- and liquid- chromatography coupled to mass spectrometry to investigate the metabolic adjustments between wild type and mmdh1 The genotypes responded similarly to high CO2 treatment both with respect to metabolite pools and (13)C incorporation during a 2-h treatment. However, under low CO2 several metabolites differed between the two genotypes and, interestingly most of these were closely associated with photorespiration. We found that while the glycine/serine ratio increased, a concomitant altered glutamine/glutamate/α-ketoglutarate relation occurred. Taken together, our results indicate that adequate mMDH activity is essential to shuttle reductants out from the mitochondria to support the photorespiratory flux, and strengthen the idea that photorespiration is tightly intertwined with peripheral metabolic reactions.

Assessing compartmentalized flux in lipid metabolism with isotopes

Metabolism in plants takes place across multiple cell types and within distinct organelles. The distributions equate to spatial heterogeneity; though the limited means to experimentally assess metabolism frequently involve homogenizing tissues and mixing metabolites from different locations. Most current isotope investigations of metabolism therefore lack the ability to resolve spatially distinct events. Recognition of this limitation has resulted in inspired efforts to advance metabolic flux analysis and isotopic labeling techniques. Though a number of these efforts have been applied to studies in central metabolism; recent advances in instrumentation and techniques present an untapped opportunity to make similar progress in lipid metabolism where the use of stable isotopes has been more limited. These efforts will benefit from sophisticated radiolabeling reports that continue to enrich our knowledge on lipid biosynthetic pathways and provide some direction for stable isotope experimental design and extension of MFA. Evidence for this assertion is presented through the review of several elegant stable isotope studies and by taking stock of what has been learned from radioisotope investigations when spatial aspects of metabolism were considered. The studies emphasize that glycerolipid production occurs across several locations with assembly of lipids in the ER or plastid, fatty acid biosynthesis occurring in the plastid, and the generation of acetyl-CoA and glycerol-3-phosphate taking place at multiple sites. Considering metabolism in this context underscores the cellular and subcellular organization that is important to enhanced production of glycerolipids in plants. An attempt is made to unify salient features from a number of reports into a diagrammatic model of lipid metabolism and propose where stable isotope labeling experiments and further flux analysis may help address questions in the field. This article is part of a Special Issue entitled: Plant Lipid Biology edited by Kent D. Chapman and Ivo Feussner.

Mathematical models of plant metabolism

Among various modeling approaches in plant metabolic research, applications of Constraint-Based modeling are fast increasing in recent years, apparently driven by current advances in genomics and genome sequencing. Constraint-Based modeling, the functional analysis of metabolic networks at the whole cell or genome scale, is more difficult to apply to plants than to microbes. Here we discuss recent developments in Constraint-Based modeling in plants with focus on issues of model reconstruction and flux prediction. Another topic is the emerging application of integration of Constraint-Based modeling with omics data to increase predictive power. Furthermore, advances in experimental measurements of cellular fluxes by (13)C-Metabolic Flux Analysis are highlighted, including instationary (13)C-MFA used to probe autotrophic metabolism in photosynthetic tissue in the light.

Omics data input for metabolic modeling

Recent advancements in high-throughput large-scale analytical methods to sequence genomes of organisms, and to quantify gene expression, proteins, lipids and metabolites have changed the paradigm of metabolic modeling. The cost of data generation and analysis has decreased significantly, which has allowed exponential increase in the amount of omics data being generated for an organism in a very short time. Compared to progress made in microbial metabolic modeling, plant metabolic modeling still remains limited due to its complex genomes and compartmentalization of metabolic reactions. Herein, we review and discuss different omics-datasets with potential application in the functional genomics. In particular, this review focuses on the application of omics-datasets towards construction and reconstruction of plant metabolic models.

Quantifying plant phenotypes with isotopic labeling & metabolic flux analysis

Analyses of metabolic flux using stable isotopes in plants have traditionally been restricted to tissues with presumed homogeneous cell populations and long metabolic steady states such as developing seeds, cell suspensions, or cultured roots and root tips. It is now possible to describe these and other metabolically more dynamic tissues such as leaves in greater detail using novel methods in mass spectrometry, isotope labeling strategies, and transient labeling-based flux analyses. Such studies are necessary for a systems level description of plant function that more closely represents biological reality, and provides insights into the genes that will need to be modified as natural resources become ever more limited and environments change.

Tobacco guard cells fix CO2 by both Rubisco and PEPcase while sucrose acts as a substrate during light-induced stomatal opening

Transcriptomic and proteomic studies have improved our knowledge of guard cell function; however, metabolic changes in guard cells remain relatively poorly understood. Here we analysed metabolic changes in guard cell-enriched epidermal fragments from tobacco during light-induced stomatal opening. Increases in sucrose, glucose and fructose were observed during light-induced stomatal opening in the presence of sucrose in the medium while no changes in starch were observed, suggesting that the elevated fructose and glucose levels were a consequence of sucrose rather than starch breakdown. Conversely, reduction in sucrose was observed during light- plus potassium-induced stomatal opening. Concomitant with the decrease in sucrose, we observed an increase in the level as well as in the (13) C enrichment in metabolites of, or associated with, the tricarboxylic acid cycle following incubation of the guard cell-enriched preparations in (13) C-labelled bicarbonate. Collectively, the results obtained support the hypothesis that sucrose is catabolized within guard cells in order to provide carbon skeletons for organic acid production. Furthermore, they provide a qualitative demonstration that CO2 fixation occurs both via ribulose-1,5-biphosphate carboxylase/oxygenase (Rubisco) and phosphoenolpyruvate carboxylase (PEPcase). The combined data are discussed with respect to current models of guard cell metabolism and function.

A roadmap for interpreting (13)C metabolite labeling patterns from cells

Measuring intracellular metabolism has increasingly led to important insights in biomedical research. (13)C tracer analysis, although less information-rich than quantitative (13)C flux analysis that requires computational data integration, has been established as a time-efficient method to unravel relative pathway activities, qualitative changes in pathway contributions, and nutrient contributions. Here, we review selected key issues in interpreting (13)C metabolite labeling patterns, with the goal of drawing accurate conclusions from steady state and dynamic stable isotopic tracer experiments.

Fluxes through plant metabolic networks: measurements, predictions, insights and challenges

Although the flows of material through metabolic networks are central to cell function, they are not easy to measure other than at the level of inputs and outputs. This is particularly true in plant cells, where the network spans multiple subcellular compartments and where the network may function either heterotrophically or photoautotrophically. For many years, kinetic modelling of pathways provided the only method for describing the operation of fragments of the network. However, more recently, it has become possible to map the fluxes in central carbon metabolism using the stable isotope labelling techniques of metabolic flux analysis (MFA), and to predict intracellular fluxes using constraints-based modelling procedures such as flux balance analysis (FBA). These approaches were originally developed for the analysis of microbial metabolism, but over the last decade, they have been adapted for the more demanding analysis of plant metabolic networks. Here, the principal features of MFA and FBA as applied to plants are outlined, followed by a discussion of the insights that have been gained into plant metabolic networks through the application of these time-consuming and non-trivial methods. The discussion focuses on how a system-wide view of plant metabolism has increased our understanding of network structure, metabolic perturbations and the provision of reducing power and energy for cell function. Current methodological challenges that limit the scope of plant MFA are discussed and particular emphasis is placed on the importance of developing methods for cell-specific MFA.

Pool size measurements facilitate the determination of fluxes at branching points in non-stationary metabolic flux analysis: the case of Arabidopsis thaliana

Pool size measurements are important for the estimation of absolute intracellular fluxes in particular scenarios based on data from heavy carbon isotope experiments. Recently, steady-state fluxes estimates were obtained for central carbon metabolism in an intact illuminated rosette of Arabidopsis thaliana grown photoautotrophically (Szecowka et al., 2013; Heise et al., 2014). Fluxes were estimated therein by integrating mass-spectrometric data of the dynamics of the unlabeled metabolic fraction, data on metabolic pool sizes, partitioning of metabolic pools between cellular compartments and estimates of photosynthetically inactive pools, with a simplified model of plant central carbon metabolism. However, the fluxes were determined by treating the pool sizes as fixed parameters. Here we investigated whether and, if so, to what extent the treatment of pool sizes as parameters to be optimized in three scenarios may affect the flux estimates. The results are discussed in terms of benchmark values for canonical pathways and reactions, including starch and sucrose synthesis as well as the ribulose-1,5-bisphosphate carboxylation and oxygenation reactions. In addition, we discuss pathways emerging from a divergent branch point for which pool sizes are required for flux estimation, irrespective of the computational approach used for the simulation of the observable labeling pattern. Therefore, our findings indicate the necessity for development of techniques for accurate pool size measurements to improve the quality of flux estimates from non-stationary flux estimates in intact plant cells in the absence of alternative flux measurements.

Moving toward a comprehensive map of central plant metabolism

Decades of intensive study have led to the discovery of the main pathways involved in central metabolism but only some of the pathways and regulatory networks in which they are embedded. In this review, we discuss techniques used to assemble these pathways into a systems biology framework that can enable accurate modeling of the response of central metabolism to changes, including ways to perturb metabolic systems and assemble the resulting data into a meaningful network. Critically, these networks are of such size and complexity that it is possible to derive them only if data from different groups can be comprehensively and meaningfully combined. We conclude that it is essential to establish common standards for the description of experimental conditions and data collection and to store this information in databases to which the whole community can contribute.

How to measure metabolic fluxes: a taxonomic guide for (13)C fluxomics

Metabolic reaction rates (fluxes) contribute fundamentally to our understanding of metabolic phenotypes and mechanisms of cellular regulation. Stable isotope-based fluxomics integrates experimental data with biochemical networks and mathematical modeling to 'measure' the in vivo fluxes within an organism that are not directly observable. In recent years, (13)C fluxomics has evolved into a technology with great experimental, analytical, and mathematical diversity. This review aims at establishing a unified taxonomy by means of which the various fluxomics methods can be compared to each other. By linking the developed modeling approaches to recent studies, their challenges and opportunities are put into perspective. The proposed classification serves as a guide for scientific 'travelers' who are striving to resolve research questions with the currently available (13)C fluxomics toolset.