Compartment-specific labeling information in 13C metabolic flux analysis of plants

13C-labeling reveals non-conventional pathways providing carbon for hydroxy fatty acid synthesis in Physaria fendleri

Physaria fendleri is a member of the Brassicaceae that produces in its embryos hydroxy fatty acids, constituents of oils that are very valuable and widely used by industry for cosmetics, lubricants, biofuels, etc. Free of toxins and rich in hydroxy fatty acids, Physaria provides a promising alternative to imported castor oil and is on the verge of being commercialized. This study aims to identify important biochemical step(s) for oil synthesis in Physaria, which may serve as target(s) for future crop improvement. To advance towards this goal, the endosperm composition was analysed by LC-MS/MS to develop and validate culture conditions that mimic the development of the embryos in planta. Using developing Physaria embryos in culture and 13C-labeling, our studies revealed that: (i) Physaria embryos metabolize carbon into biomass with an efficiency significantly lower than other photosynthetic embryos; (ii) the plastidic malic enzyme provides 42% of the pyruvate used for de novo fatty acid synthesis, which is the highest measured so far in developing 'green' oilseed embryos; and (iii) Physaria uses non-conventional pathways to channel carbon into oil, namely the Rubisco shunt, which fixes CO2 released in the plastid, and the reversibility of isocitrate dehydrogenase, which provides additional carbon for fatty acid elongation.

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 pathogen-specific isotope tracing approach reveals metabolic activities and fluxes of intracellular Salmonella

Pathogenic bacteria proliferating inside mammalian host cells need to rapidly adapt to the intracellular environment. How they achieve this and scavenge essential nutrients from the host has been an open question due to the difficulties in distinguishing between bacterial and host metabolites in situ. Here, we capitalized on the inability of mammalian cells to metabolize mannitol to develop a stable isotopic labeling approach to track Salmonella enterica metabolites during intracellular proliferation in host macrophage and epithelial cells. By measuring label incorporation into Salmonella metabolites with liquid chromatography-mass spectrometry (LC-MS), and combining it with metabolic modeling, we identify relevant carbon sources used by Salmonella, uncover routes of their metabolization, and quantify relative reaction rates in central carbon metabolism. Our results underline the importance of the Entner-Doudoroff pathway (EDP) and the phosphoenolpyruvate carboxylase for intracellularly proliferating Salmonella. More broadly, our metabolic labeling strategy opens novel avenues for understanding the metabolism of pathogens inside host cells.

Progress in understanding and improving oil content and quality in seeds

The world's population is projected to increase by two billion by 2050, resulting in food and energy insecurity. Oilseed crops have been identified as key to address these challenges: they produce and store lipids in the seeds as triacylglycerols that can serve as a source of food/feed, renewable fuels, and other industrially-relevant chemicals. Therefore, improving seed oil content and composition has generated immense interest. Research efforts aiming to unravel the regulatory pathways involved in fatty acid synthesis and to identify targets for metabolic engineering have made tremendous progress. This review provides a summary of the current knowledge of oil metabolism and discusses how photochemical activity and unconventional pathways can contribute to high carbon conversion efficiency in seeds. It also highlights the importance of 13C-metabolic flux analysis as a tool to gain insights on the pathways that regulate oil biosynthesis in seeds. Finally, a list of key genes and regulators that have been recently targeted to enhance seed oil production are reviewed and additional possible targets in the metabolic pathways are proposed to achieve desirable oil content and quality.

Compartment-specific metabolome labeling enables the identification of subcellular fluxes that may serve as promising metabolic engineering targets in CHO cells

¹³C labeling data are used to calculate quantitative intracellular flux patterns reflecting in vivo conditions. Given that approaches for compartment-specific metabolomics exist, the benefits they offer compared to conventional non-compartmented ¹³C flux studies remain to be determined. Using compartment-specific labeling information of IgG1-producing Chinese hamster ovary cells, this study investigated differences of flux patterns exploiting and ignoring metabolic labeling data of cytosol and mitochondria. Although cellular analysis provided good estimates for the majority of intracellular fluxes, half of the mitochondrial transporters, and NADH and ATP balances, severe differences were found for some reactions. Accurate flux estimations of almost all iso-enzymes heavily depended on the sub-cellular labeling information. Furthermore, key discrepancies were found for the mitochondrial carriers v_AGC1 (Aspartate/Glutamate antiporter), v_DIC (Malate/H⁺ symporter), and v_OGC (α-ketoglutarate/malate antiporter). Special emphasis is given to the flux of cytosolic malic enzyme (v_ME): it could not be estimated without the compartment-specific malate labeling information. Interesting enough, cytosolic malic enzyme is an important metabolic engineering target for improving cell-specific IgG1 productivity. Hence, compartment-specific ¹³C labeling analysis serves as prerequisite for related metabolic engineering studies.

Analyzing Mass Spectrometry Imaging Data of 13C-Labeled Phospholipids in Camelina sativa and Thlaspi arvense (Pennycress) Embryos

The combination of ¹³C-isotopic labeling and mass spectrometry imaging (MSI) offers an approach to analyze metabolic flux in situ. However, combining isotopic labeling and MSI presents technical challenges ranging from sample preparation, label incorporation, data collection, and analysis. Isotopic labeling and MSI individually create large, complex data sets, and this is compounded when both methods are combined. Therefore, analyzing isotopically labeled MSI data requires streamlined procedures to support biologically meaningful interpretations. Using currently available software and techniques, here we describe a workflow to analyze ¹³C-labeled isotopologues of the membrane lipid and storage oil lipid intermediate―phosphatidylcholine (PC). Our results with embryos of the oilseed crops, Camelina sativa and Thlaspi arvense (pennycress), demonstrated greater ¹³C-isotopic labeling in the cotyledons of developing embryos compared with the embryonic axis. Greater isotopic enrichment in PC molecular species with more saturated and longer chain fatty acids suggest different flux patterns related to fatty acid desaturation and elongation pathways. The ability to evaluate MSI data of isotopically labeled plant embryos will facilitate the potential to investigate spatial aspects of metabolic flux in situ.

Metabolic Flux Analysis-Linking Isotope Labeling and Metabolic Fluxes

Metabolic flux analysis (MFA) is an increasingly important tool to study metabolism quantitatively. Unlike the concentrations of metabolites, the fluxes, which are the rates at which intracellular metabolites interconvert, are not directly measurable. MFA uses stable isotope labeled tracers to reveal information related to the fluxes. The conceptual idea of MFA is that in tracer experiments the isotope labeling patterns of intracellular metabolites are determined by the fluxes, therefore by measuring the labeling patterns we can infer the fluxes in the network. In this review, we will discuss the basic concept of MFA using a simplified upper glycolysis network as an example. We will show how the fluxes are reflected in the isotope labeling patterns. The central idea we wish to deliver is that under metabolic and isotopic steady-state the labeling pattern of a metabolite is the flux-weighted average of the substrates’ labeling patterns. As a result, MFA can tell the relative contributions of converging metabolic pathways only when these pathways make substrates in different labeling patterns for the shared product. This is the fundamental principle guiding the design of isotope labeling experiment for MFA including tracer selection. In addition, we will also discuss the basic biochemical assumptions of MFA, and we will show the flux-solving procedure and result evaluation. Finally, we will highlight the link between isotopically stationary and nonstationary flux analysis.

Towards model-driven characterization and manipulation of plant lipid metabolism

Plant lipids have versatile applications and provide essential fatty acids in human diet. Therefore, there has been a growing interest to better characterize the genetic basis, regulatory networks, and metabolic pathways that shape lipid quantity and composition. Addressing these issues is challenging due to context-specificity of lipid metabolism integrating environmental, developmental, and tissue-specific cues. Here we systematically review the known metabolic pathways and regulatory interactions that modulate the levels of storage lipids in oilseeds. We argue that the current understanding of lipid metabolism provides the basis for its study in the context of genome-wide plant metabolic networks with the help of approaches from constraint-based modeling and metabolic flux analysis. The focus is on providing a comprehensive summary of the state-of-the-art of modeling plant lipid metabolic pathways, which we then contrast with the existing modeling efforts in yeast and microalgae. We then point out the gaps in knowledge of lipid metabolism, and enumerate the recent advances of using genome-wide association and quantitative trait loci mapping studies to unravel the genetic regulations of lipid metabolism. Finally, we offer a perspective on how advances in the constraint-based modeling framework can propel further characterization of plant lipid metabolism and its rational manipulation.

Non-conventional pathways enable pennycress (Thlaspi arvense L.) embryos to achieve high efficiency of oil biosynthesis

Pennycress (Thlaspi arvense L.) accumulates oil up to 35% of the total seed biomass, and its overall fatty acid composition is suitable for aviation fuel. However, for this plant to become economically viable, its oil production needs to be improved. In vivo culture conditions that resemble the development of pennycress embryos in planta were developed based on the composition of the liquid endosperm. Then, substrate uptake rates and biomass accumulation were measured from cultured pennycress embryos, revealing a biosynthetic efficiency of 93%, which is one of the highest in comparison with other oilseeds to date. Additionally, the ratio of carbon in oil to CO2 indicated that non-conventional pathways are likely to be responsible for such a high carbon conversion efficiency. To identify the reactions enabling this phenomenon, parallel labeling experiments with 13C-labeled substrates were conducted in pennycress embryos. The main findings of these labeling experiments include: (i) the occurrence of the oxidative reactions of the pentose phosphate pathway in the cytosol; (ii) the reversibility of isocitrate dehydrogenase; (iii) the operation of the plastidic NADP-dependent malic enzyme; and (iv) the refixation of CO2 by Rubisco. These reactions are key providers of carbon and reductant for fatty acid synthesis and elongation.

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.

Liquid Chromatography Tandem Mass Spectrometry Quantification of 13C-Labeling in Sugars

Subcellular compartmentation has been challenging in plant ¹³C-metabolic flux analysis. Indeed, plant cells are highly compartmented: they contain vacuoles and plastids in addition to the regular organelles found in other eukaryotes. The distinction of reactions between compartments is possible when metabolites are synthesized in a particular compartment or by a unique pathway. Sucrose is an example of such a metabolite: it is specifically produced in the cytosol from glucose 6-phosphate (G6P) and fructose 6-phosphate (F6P). Therefore, determining the ¹³C-labeling in the fructosyl and glucosyl moieties of sucrose directly informs about the labeling of cytosolic F6P and G6P, respectively. To date, the most commonly used method to monitor sucrose labeling is by nuclear magnetic resonance, which requires substantial amounts of biological sample. This study describes a new methodology that accurately measures the labeling in free sugars using liquid chromatography tandem mass spectrometry (LC-MS/MS). For this purpose, maize embryos were pulsed with [U-¹³C]-fructose, intracellular sugars were extracted, and their time-course labeling was analyzed by LC-MS/MS. Additionally, extracts were enzymatically treated with hexokinase to remove the soluble hexoses, and then invertase to cleave sucrose into fructose and glucose. Finally, the labeling in the glucosyl and fructosyl moieties of sucrose was determined by LC-MS/MS.

Tracing metabolic flux through time and space with isotope labeling experiments

Metabolism is dynamic and must function in context-specific ways to adjust to changes in the surrounding cellular and ecological environment. When isotopic tracers are used, metabolite flow (i.e. metabolic flux) can be quantified through biochemical networks to assess metabolic pathway operation. The cellular activities considered across multiple tissues and organs result in the observed phenotype and can be analyzed to discover emergent, whole-system properties of biology and elucidate misconceptions about network operation. However, temporal and spatial challenges remain significant hurdles and require novel approaches and creative solutions. We survey current investigations in higher plant and animal systems focused on dynamic isotope labeling experiments, spatially resolved measurement strategies, and observations from re-analysis of our own studies that suggest prospects for future work. Related discoveries will be necessary to push the frontier of our understanding of metabolism to suggest novel solutions to cure disease and feed a growing future world population.

Provision of carbon skeleton for lipid synthesis from the breakdown of intracellular protein and soluble sugar in Phaeodactylum tricornutum under high CO2

BACKGROUND

Increasing CO₂ emissions have resulted in ocean acidification, affecting marine plant photosynthesis and changing the nutrient composition of marine ecosystems. The physiological and biochemical processes of marine phytoplankton in response to ocean acidification have been reported, but have been mainly focused on growth and photosynthetic physiology. To acquire a thorough knowledge of the molecular regulation mechanisms, model species with clear genetic background should be selected for systematic study. Phaeodactylum tricornutum is a pennate diatom with the characteristics of small genome size, short generation cycle, and easy to transform. Furthermore, the genome of P. tricornutum has been completely sequenced.

RESULTS AND DISCUSSION

In this study, P. tricornutum was cultured at high and normal CO₂ concentrations. Cell composition changes during culture time were investigated. The ¹³C isotope tracing technique was used to determine fractional labeling enrichments for the main cellular components. The results suggested that when lipid content increased significantly under high CO₂ conditions, total protein and soluble sugar contents decreased. The ¹³C labeling experiment indicated that the C skeleton needed for fatty acid C chain elongation in lipid synthesis under high CO₂ conditions is not mainly derived from NaHCO₃ (carbon fixed by photosynthesis).

CONCLUSION

This study indicated that breakdown of intracellular protein and soluble sugar provide C skeleton for lipid synthesis under high CO₂ concentration.

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 challenge and potential of photosynthesis: unique considerations for metabolic flux measurements in photosynthetic microorganisms

Photosynthetic microorganisms have the potential for sustainable production of chemical feedstocks and products but have had limited success due to a lack of tools and deeper understanding of metabolic pathway regulation. The application of instationary metabolic flux analysis (INST-MFA) to photosynthetic microorganisms has allowed researchers to quantify fluxes and identify bottlenecks and metabolic inefficiencies to improve strain performance or gain insight into cellular physiology. Additionally, flux measurements can also highlight deviations between measured and predicted fluxes, revealing weaknesses in metabolic models and highlighting areas where a lack of understanding still exists. In this review, we outline the experimental steps necessary to successfully perform photosynthetic flux experiments and analysis. We also discuss the challenges unique to photosynthetic microorganisms and how to account for them, including: light supply, quenching, concentration, extraction, analysis, and flux calculation. We hope that this will enable a larger number of researchers to successfully apply isotope assisted metabolic flux analysis (¹³C-MFA) to their favorite photosynthetic organism.

Understanding metabolism with flux analysis: From theory to application

Quantitative and qualitative knowledge of metabolic rates (i.e. fluxes) over a metabolic network and in specific cellular compartments gives insights into the regulation of metabolism and helps to understand the contribution of metabolic alterations to pathology. In this review we introduce methodology to resolve metabolic fluxes from stable isotope labeling and relevant techniques in model development, model simplification, flux uncertainty analysis and experimental design that together is termed metabolic flux analysis. Finally we discuss applications using metabolic flux analysis to elucidate mechanisms pertinent to tumor cell metabolism. We hope that this review gives the readers a brief introduction of how flux analysis is conducted, how technical issues related to it are addressed, and how its application has contributed to our knowledge of tumor cell metabolism.

Revealing the mystery of metabolic adaptations using a genome scale model of Leishmania infantum

Human macrophage phagolysosome and sandfly midgut provide antagonistic ecological niches for Leishmania parasites to survive and proliferate. Parasites optimize their metabolism to utilize the available inadequate resources by adapting to those environments. Lately, a number of metabolomics studies have revived the interest to understand metabolic strategies utilized by the Leishmania parasite for optimal survival within its hosts. For the first time, we propose a reconstructed genome-scale metabolic model for Leishmania infantum JPCM5, the analyses of which not only captures observations reported by metabolomics studies in other Leishmania species but also divulges novel features of the L. infantum metabolome. Our results indicate that Leishmania metabolism is organized in such a way that the parasite can select appropriate alternatives to compensate for limited external substrates. A dynamic non-essential amino acid motif exists within the network that promotes a restricted redistribution of resources to yield required essential metabolites. Further, subcellular compartments regulate this metabolic re-routing by reinforcing the physiological coupling of specific reactions. This unique metabolic organization is robust against accidental errors and provides a wide array of choices for the parasite to achieve optimal survival.

Metabolic flux analysis of heterotrophic growth in Chlamydomonas reinhardtii

Despite the wealth of knowledge available for C. reinhardtii, the central metabolic fluxes of growth on acetate have not yet been determined. In this study, ¹³C-metabolic flux analysis (¹³C-MFA) was used to determine and quantify the metabolic pathways of primary metabolism in C. reinhardtii cells grown under heterotrophic conditions with acetate as the sole carbon source. Isotopic labeling patterns of compartment specific biomass derived metabolites were used to calculate the fluxes. It was found that acetate is ligated with coenzyme A in the three subcellular compartments (cytosol, mitochondria and plastid) included in the model. Two citrate synthases were found to potentially be involved in acetyl-coA metabolism; one localized in the mitochondria and the other acting outside the mitochondria. Labeling patterns demonstrate that Acetyl-coA synthesized in the plastid is directly incorporated in synthesis of fatty acids. Despite having a complete TCA cycle in the mitochondria, it was also found that a majority of the malate flux is shuttled to the cytosol and plastid where it is converted to oxaloacetate providing reducing equivalents to these compartments. When compared to predictions by flux balance analysis, fluxes measured with ¹³C-MFA were found to be suboptimal with respect to biomass yield; C. reinhardtii sacrifices biomass yield to produce ATP and reducing equivalents.

Plant lipidomics at the crossroads: From technology to biology driven science

The identification and quantification of lipids from plant tissues have become commonplace and many researchers now incorporate lipidomics approaches into their experimental studies. Plant lipidomics research continues to involve technological developments such as those in mass spectrometry imaging, but in large part, lipidomics approaches have matured to the point of being accessible to the novice. Here we review some important considerations for those planning to apply plant lipidomics to their biological questions, and offer suggestions for appropriate tools and practices. This article is part of a Special Issue entitled: BBALIP_Lipidomics Opinion Articles edited by Sepp Kohlwein.

Biochemical precursor effects on the fatty acid production in cell suspension cultures of Theobroma cacao L

Cocoa butter (CB) is composed of 96% palmitic, stearic, oleic, linoleic and linolenic fatty acids that are responsible for the hardness, texture and fusion properties of chocolate. Through in vitro plant cell culture it is possible to modify CB lipid profiles and to study the fatty acid biosynthesis pathway on a subcellular level, evaluating fundamental aspects to enhance in vitro fatty acid production in a specific and controlled way. In this research, culture media was supplemented with acetate, biotin, pyruvate, bicarbonate and glycerol at three different concentrations and the effects on the biomass production (g/L), cell viability, and fatty acids profile and production was evaluated in in vitro cell suspensions culture. It was found that biotin stimulated fatty acid synthesis without altering cell viability and cell growth. It was also evident a change in the lipid profile of cell suspensions, increasing middle and long chain fatty acids proportion, which are unusual to those reported in seeds; thus implying that it is possible to modify lipid profiles according to the treatment used. According to the results of sucrose gradients and enzyme assays performed, it is proposed that cacao cells probably use the pentose phosphate pathway, mitochondria being the key organelle in the carbon flux for the synthesis of reductant power and fatty acid precursors.

Isotopically Nonstationary Metabolic Flux Analysis (INST-MFA) of Photosynthesis and Photorespiration in Plants

Photorespiration is a central component of photosynthesis; however to better understand its role it should be viewed in the context of an integrated metabolic network rather than a series of individual reactions that operate independently. Isotopically nonstationary ¹³C metabolic flux analysis (INST-MFA), which is based on transient labeling studies at metabolic steady state, offers a comprehensive platform to quantify plant central metabolism. In this chapter, we describe the application of INST-MFA to investigate metabolism in leaves. Leaves are an autotrophic tissue, assimilating CO₂ over a diurnal period implying that the metabolic steady state is limited to less than 12 h and thus requiring an INST-MFA approach. This strategy results in a comprehensive unified description of photorespiration, Calvin cycle, sucrose and starch synthesis, tricarboxylic acid (TCA) cycle, and amino acid biosynthetic fluxes. We present protocols of the experimental aspects for labeling studies: transient ¹³CO₂ labeling of leaf tissue, sample quenching and extraction, mass spectrometry (MS) analysis of isotopic labeling data, measurement of sucrose and amino acids in vascular exudates, and provide details on the computational flux estimation using INST-MFA.

Metabolic flux analyses of Pseudomonas aeruginosa cystic fibrosis isolates

Pseudomonas aeruginosa is a metabolically versatile wide-ranging opportunistic pathogen. In humans P. aeruginosa causes infections of the skin, urinary tract, blood, and the lungs of Cystic Fibrosis patients. In addition, P. aeruginosa's broad environmental distribution, relatedness to biotechnologically useful species, and ability to form biofilms have made it the focus of considerable interest. We used ¹³C metabolic flux analysis (MFA) and flux balance analysis to understand energy and redox production and consumption and to explore the metabolic phenotypes of one reference strain and five strains isolated from the lungs of cystic fibrosis patients. Our results highlight the importance of the oxidative pentose phosphate and Entner-Doudoroff pathways in P. aeruginosa growth. Among clinical strains we report two divergent metabolic strategies and identify changes between genetically related strains that have emerged during a chronic infection of the same patient. MFA revealed that the magnitude of fluxes through the glyoxylate cycle correlates with growth rates.

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.

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.

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

Metabolism is comprised of networks of chemical transformations, organized into integrated biochemical pathways that are the basis of cellular operation, and function to sustain life. Metabolism, and thus life, is not static. The rate of metabolites transitioning through biochemical pathways (i.e., flux) determines cellular phenotypes, and is constantly changing in response to genetic or environmental perturbations. Each change evokes a response in metabolic pathway flow, and the quantification of fluxes under varied conditions helps to elucidate major and minor routes, and regulatory aspects of metabolism. To measure fluxes requires experimental methods that assess the movements and transformations of metabolites without creating artifacts. Isotopic labeling fills this role and is a long-standing experimental approach to identify pathways and quantify their metabolic relevance in different tissues or under different conditions. The application of labeling techniques to plant science is however far from reaching it potential. In light of advances in genetics and molecular biology that provide a means to alter metabolism, and given recent improvements in instrumentation, computational tools and available isotopes, the use of isotopic labeling to probe metabolism is becoming more and more powerful. We review the principal analytical methods for isotopic labeling with a focus on seminal studies of pathways and fluxes in lipid metabolism and carbon partitioning through central metabolism. Central carbon metabolic steps are directly linked to lipid production by serving to generate the precursors for fatty acid biosynthesis and lipid assembly. Additionally some of the ideas for labeling techniques that may be most applicable for lipid metabolism in the future were originally developed to investigate other aspects of central metabolism. We conclude by describing recent advances that will play an important future role in quantifying flux and metabolic operation in plant tissues.

The response of Chlamydomonas reinhardtii to nitrogen deprivation: a systems biology analysis

Drastic alteration in macronutrients causes large changes in gene expression in the photosynthetic unicellular alga Chlamydomonas reinhardtii. Preliminary data suggested that cells follow a biphasic response to this change hinging on the initiation of lipid accumulation, and we hypothesized that drastic repatterning of metabolism also followed this biphasic modality. To test this hypothesis, transcriptomic, proteomic, and metabolite changes that occur under nitrogen (N) deprivation were analyzed. Eight sampling times were selected covering the progressive slowing of growth and induction of oil synthesis between 4 and 6 h after N deprivation. Results of the combined, systems-level investigation indicated that C. reinhardtii cells sense and respond on a large scale within 30 min to a switch to N-deprived conditions turning on a largely gluconeogenic metabolic state, which then transitions to a glycolytic stage between 4 and 6 h after N depletion. This nitrogen-sensing system is transduced to carbon- and nitrogen-responsive pathways, leading to down-regulation of carbon assimilation and chlorophyll biosynthesis, and an increase in nitrogen metabolism and lipid biosynthesis. For example, the expression of nearly all the enzymes for assimilating nitrogen from ammonium, nitrate, nitrite, urea, formamide/acetamide, purines, pyrimidines, polyamines, amino acids and proteins increased significantly. Although arginine biosynthesis enzymes were also rapidly up-regulated, arginine pool size changes and isotopic labeling results indicated no increased flux through this pathway.

Multi-Spectroscopic Analysis of Seed Quality and 13C-Stable-Iotopologue Monitoring in Initial Growth Metabolism of Jatropha curcas L

In the present study, we applied nuclear magnetic resonance (NMR), as well as near-infrared (NIR) spectroscopy, to Jatropha curcas to fulfill two objectives: (1) to qualitatively examine the seeds stored at different conditions, and (2) to monitor the metabolism of J. curcas during its initial growth stage under stable-isotope-labeling condition (until 15 days after seeding). NIR spectra could non-invasively distinguish differences in storage conditions. NMR metabolic analysis of water-soluble metabolites identified sucrose and raffinose family oligosaccharides as positive markers and gluconic acid as a negative marker of seed germination. Isotopic labeling patteren of metabolites in germinated seedlings cultured in agar-plate containg 13C-glucose and 15N-nitrate was analyzed by zero-quantum-filtered-total correlation spectroscopy (ZQF-TOCSY) and 13C-detected 1H-13C heteronuclear correlation spectroscopy (HETCOR). 13C-detected HETOCR with 13C-optimized cryogenic probe provided high-resolution 13C-NMR spectra of each metabolite in molecular crowd. The 13C-13C/12C bondmer estimated from 1H-13C HETCOR spectra indicated that glutamine and arginine were the major organic compounds for nitrogen and carbon transfer from roots to leaves.

(13)C metabolic flux analysis of recombinant expression hosts

Identifying host cell metabolic phenotypes that promote high recombinant protein titer is a major goal of the biotech industry. (13)C metabolic flux analysis (MFA) provides a rigorous approach to quantify these metabolic phenotypes by applying isotope tracers to map the flow of carbon through intracellular metabolic pathways. Recent advances in tracer theory and measurements are enabling more information to be extracted from (13)C labeling experiments. Sustained development of publicly available software tools and standardization of experimental workflows is simultaneously encouraging increased adoption of (13)C MFA within the biotech research community. A number of recent (13)C MFA studies have identified increased citric acid cycle and pentose phosphate pathway fluxes as consistent markers of high recombinant protein expression, both in mammalian and microbial hosts. Further work is needed to determine whether redirecting flux into these pathways can effectively enhance protein titers while maintaining acceptable glycan profiles.

Analysis of isotopic labeling in peptide fragments by tandem mass spectrometry

Phenotype in multicellular organisms is the consequence of dynamic metabolic events that occur in a spatially dependent fashion. This spatial and temporal complexity presents challenges for investigating metabolism; creating a need for improved methods that effectively probe biochemical events such as amino acid biosynthesis. Isotopic labeling can provide a temporal-spatial recording of metabolic events through, for example, the description of enriched amino acids in the protein pool. Proteins are therefore an important readout of metabolism and can be assessed with modern mass spectrometers. We compared the measurement of isotopic labeling in MS2 spectra obtained from tandem mass spectrometry under either higher energy collision dissociation (HCD) or collision induced dissociation (CID) at varied energy levels. Developing soybean embryos cultured with or without 13C-labeled substrates, and Escherichia coli MG1655 enriched by feeding 7% uniformly labeled glucose served as a source of biological material for protein evaluation. CID with low energies resulted in a disproportionate amount of heavier isotopologues remaining in the precursor isotopic distribution. HCD resulted in fewer quantifiable products; however deviation from predicted distributions were small relative to the CID-based comparisons. Fragment ions have the potential to provide information on the labeling of amino acids in peptides, but our results indicate that without further development the use of this readout in quantitative methods such as metabolic flux analysis is limited.

Quantification of peptide m/z distributions from 13C-labeled cultures with high-resolution mass spectrometry

Isotopic labeling studies of primary metabolism frequently utilize GC/MS to quantify (13)C in protein-hydrolyzed amino acids. During processing some amino acids are degraded, which reduces the size of the measurement set. The advent of high-resolution mass spectrometers provides a tool to assess molecular masses of peptides with great precision and accuracy and computationally infer information about labeling in amino acids. Amino acids that are isotopically labeled during metabolism result in labeled peptides that contain spatial and temporal information that is associated with the biosynthetic origin of the protein. The quantification of isotopic labeling in peptides can therefore provide an assessment of amino acid metabolism that is specific to subcellular, cellular, or temporal conditions. A high-resolution orbital trap was used to quantify isotope labeling in peptides that were obtained from unlabeled and isotopically labeled soybean embryos and Escherichia coli cultures. Standard deviations were determined by estimating the multinomial variance associated with each element of the m/z distribution. Using the estimated variance, quantification of the m/z distribution across multiple scans was achieved by a nonlinear fitting approach. Observed m/z distributions of uniformly labeled E. coli peptides indicated no significant differences between observed and simulated m/z distributions. Alternatively, amino acid m/z distributions obtained from GC/MS were convolved to simulate peptide m/z distributions but resulted in distinct profiles due to the production of protein prior to isotopic labeling. The results indicate that peptide mass isotopologue measurements faithfully represent mass distributions, are suitable for quantification of isotope-labeling-based studies, and provide additional information over existing methods.

Metabolic flux analysis using ¹³C peptide label measurements

¹³C metabolic flux analysis (MFA) has become the experimental method of choice to investigate the cellular metabolism of microbes, cell cultures and plant seeds. Conventional steady-state MFA utilizes isotopic labeling measurements of amino acids obtained from protein hydrolysates. To retain spatial information in conventional steady-state MFA, tissues or subcellular fractions must be dissected or biochemically purified. In contrast, peptides retain their identity in complex protein extracts, and may therefore be associated with a specific time of expression, tissue type and subcellular compartment. To enable 'single-sample' spatially and temporally resolved steady-state flux analysis, we investigated the suitability of peptide mass distributions (PMDs) as an alternative to amino acid label measurements. PMDs are the discrete convolution of the mass distributions of the constituent amino acids of a peptide. We investigated the requirements for the unique deconvolution of PMDs into amino acid mass distributions (AAMDs), the influence of peptide sequence length on parameter sensitivity, and how AAMD and flux estimates that are determined through deconvolution compare to estimates from a conventional GC-MS measurement-based approach. Deconvolution of PMDs of the storage protein β-conglycinin of soybean (Glycine max) resulted in good AAMD and flux estimates if fluxes were directly fitted to PMDs. Unconstrained deconvolution resulted in inferior AAMD and flux estimates. PMD measurements do not include amino acid backbone fragments, which increase the information content in GC-MS-derived analyses. Nonetheless, the resulting flux maps were of comparable quality due to the precision of Orbitrap quantification and the larger number of peptide measurements.

Quantification of stable isotope label in metabolites via mass spectrometry

Isotope labelling experiments with stable or radioactive isotopes have long been an integral part of biological and medical research. Labelling experiments led to the discovery of new metabolic pathways and made it possible to calculate the fluxes responsible for a metabolic phenotype, i.e., the qualitative and quantitative composition of metabolites in a biological system. Prerequisite for efficient isotope labelling experiments is a reliable and precise method to analyze the redistribution of isotope label in a metabolic network. Here we describe the use of the CORRECTOR program, which utilizes matrix calculations to correct mass spectral data from stable isotope labelling experiments for the distorting effect of naturally occurring stable isotopes (NOIs). CORRECTOR facilitates and speeds up the routine quantification of experimentally introduced isotope label from multiple mass spectral readouts, which are generated by routine metabolite profiling when combined with stable isotope labelling experiments.

High-throughput data pipelines for metabolic flux analysis in plants

In this chapter we illustrate the methodology for high-throughput metabolic flux analysis. Central to this is developing an end to end data pipeline, crucial for integrating the wet lab experiments and analytics, combining hardware and software automation, and standardizing data representation providing importers and exporters to support third party tools. The use of existing software at the start, data extraction from the chromatogram, and the end, MFA analysis, allows for the most flexibility in this workflow. Developing iMS2Flux provided a standard, extensible, platform independent tool to act as the "glue" between these end points. Most importantly this tool can be easily adapted to support different data formats, data verification and data correction steps allowing it to be central to managing the data necessary for high-throughput MFA. An additional tool was needed to automate the MFA software and in particular to take advantage of the course grained parallel nature of high-throughput analysis and available high performance computing facilities.In combination these methods show the development of high-throughput pipelines that allow metabolic flux analysis to join as a full member of the omics family.

Isotopomer measurement techniques in metabolic flux analysis II: mass spectrometry

Mass spectrometry (MS) offers a sensitive, reliable, and highly accurate method for measurement of isotopic labeling, which is required for generating comprehensive flux maps using metabolic flux analysis (MFA). We present protocols for assessing isotope labeling in a wide range of biochemical species, including proteinogenic amino acids, free organic and amino acids, sugar phosphates, lipids, starch-glucose, and RNA-ribose. We describe the steps of sample preparation, MS analysis, and data handling required to obtain high-quality isotope labeling measurements that are applicable to MFA. By selecting target analytes that maximize identifiability of the key fluxes of interest, MS measurements of isotope labeling can provide a powerful platform for assessing metabolic fluxes in complex biochemical networks.

Liquid chromatography tandem mass spectrometry for measuring ¹³C-labeling in intermediates of the glycolysis and pentose phosphate pathway

This chapter describes a procedure to analyze (13)C-labeled phosphorylated compounds by liquid chromatography tandem mass spectrometry. Phosphorylated compounds, intermediaries of the glycolysis and pentose phosphate pathway, are separated by anion exchange chromatography and their isotopic labeling is determined by mass spectrometry. A sensitivity in the fmole range is achieved using scheduled multiple reaction monitoring mode.

Quantification of ¹³C enrichments and isotopomer abundances for metabolic flux analysis using 1D NMR spectroscopy

The analysis of stable isotope incorporation following feeding of (13)C-labeled precursors to plant tissues provides the constraints necessary for metabolic flux analysis. This protocol describes the use of one-dimensional (1)H and (13)C nuclear magnetic resonance spectroscopy for the quantification of (13)C enrichments and isotopomer abundances in mixtures of metabolites or hydrolyzed biomass components.

Isotopomer measurement techniques in metabolic flux analysis I: nuclear magnetic resonance

Two-dimensional [(1)H, (13)C] heteronuclear single quantum correlation (HSQC) spectroscopy nuclear magnetic resonance (NMR) is a comprehensive tool in metabolic flux analysis using (13)C-labeling experiments. NMR is particularly relevant when extensive isotopomer measurements are required, such as for plant cells and tissues, which contain multiple cellular compartments. Several isotope isomers (isotopomers) can be detected and their distribution extracted quantitatively from a single 2-D HSQC NMR spectrum. For example, 2-D HSQC detects the labeling patterns of adjacent carbon atoms and provides the enrichment of individual carbon atoms of the amino acids and glucosyl and mannosyl units present in hydrolysates of glycosylated protein. The HSQC analysis can quantitatively distinguish differences between the glucosyl units in the starch hydrolysate and a protein hydrolysate of plant biomass: this specifies crucial information about compartmentalization in the plant system. The peak structures obtained from the HSQC experiment show multiplet patterns that are directly related to the isotopomer abundances. These abundances have a nonlinear relationship to the fluxes via isotopomer balancing. Fluxes are obtained from the numerical solution of these balances and a stoichiometric model that includes biomass composition data as well as consumption rates of carbohydrate and nitrogen sources. Herein, we describe the methods for the experimental measurements for flux analysis, i.e., determination of the biomass composition (lipid, protein, soluble sugar, and starch) as well as detailed procedures of acid hydrolysis of protein and starch samples and NMR sample preparation, using soybean embryo culture as the model plant system. Techniques to obtain the relative intensity of 16 amino acids and glucosyl units for protein hydrolysate and the glucosyl units of starch hydrolysate of soybean embryos in 2-D HSQC NMR spectra also are provided.

Application of metabolic flux analysis to plants

This volume compiles a series of chapters that cover the major aspects of plant metabolic flux analysis, such as but not limited to labeling of plant material, acquisition of labeling data, mathematical modeling of metabolic network at the cell, tissue, and plant level. A short revue, including methodological points and applications of flux analysis to plants, is presented in this introductory chapter.

Changes in RNA Splicing in Developing Soybean (Glycine max) Embryos

Developing soybean seeds accumulate oils, proteins, and carbohydrates that are used as oxidizable substrates providing metabolic precursors and energy during seed germination. The accumulation of these storage compounds in developing seeds is highly regulated at multiple levels, including at transcriptional and post-transcriptional regulation. RNA sequencing was used to provide comprehensive information about transcriptional and post-transcriptional events that take place in developing soybean embryos. Bioinformatics analyses lead to the identification of different classes of alternatively spliced isoforms and corresponding changes in their levels on a global scale during soybean embryo development. Alternative splicing was associated with transcripts involved in various metabolic and developmental processes, including central carbon and nitrogen metabolism, induction of maturation and dormancy, and splicing itself. Detailed examination of selected RNA isoforms revealed alterations in individual domains that could result in changes in subcellular localization of the resulting proteins, protein-protein and enzyme-substrate interactions, and regulation of protein activities. Different isoforms may play an important role in regulating developmental and metabolic processes occurring at different stages in developing oilseed embryos.

Analysis of metabolic flux using dynamic labelling and metabolic modelling

Metabolic fluxes and the capacity to modulate them are a crucial component of the ability of the plant cell to react to environmental perturbations. Our ability to quantify them and to attain information concerning the regulatory mechanisms that control them is therefore essential to understand and influence metabolic networks. For all but the simplest of flux measurements labelling methods have proven to be the most informative. Both steady-state and dynamic labelling approaches have been adopted in the study of plant metabolism. Here the conceptual basis of these complementary approaches, as well as their historical application in microbial, mammalian and plant sciences, is reviewed, and an update on technical developments in label distribution analyses is provided. This is supported by illustrative cases studies involving the kinetic modelling of secondary metabolism. One issue that is particularly complex in the analysis of plant fluxes is the extensive compartmentation of the plant cell. This problem is discussed from both theoretical and experimental perspectives, and the current approaches used to address it are assessed. Finally, current limitations and future perspectives of kinetic modelling of plant metabolism are discussed.

Metabolic and Transcriptional Reprogramming in Developing Soybean (Glycine max) Embryos

Soybean (Glycine max) seeds are an important source of seed storage compounds, including protein, oil, and sugar used for food, feed, chemical, and biofuel production. We assessed detailed temporal transcriptional and metabolic changes in developing soybean embryos to gain a systems biology view of developmental and metabolic changes and to identify potential targets for metabolic engineering. Two major developmental and metabolic transitions were captured enabling identification of potential metabolic engineering targets specific to seed filling and to desiccation. The first transition involved a switch between different types of metabolism in dividing and elongating cells. The second transition involved the onset of maturation and desiccation tolerance during seed filling and a switch from photoheterotrophic to heterotrophic metabolism. Clustering analyses of metabolite and transcript data revealed clusters of functionally related metabolites and transcripts active in these different developmental and metabolic programs. The gene clusters provide a resource to generate predictions about the associations and interactions of unknown regulators with their targets based on “guilt-by-association” relationships. The inferred regulators also represent potential targets for future metabolic engineering of relevant pathways and steps in central carbon and nitrogen metabolism in soybean embryos and drought and desiccation tolerance in plants.

The metabolic flux phenotype of heterotrophic Arabidopsis cells reveals a complex response to changes in nitrogen supply

The extent to which individual plants utilise nitrate and ammonium, the two principal nitrogen sources in the rhizosphere, is variable and many species require a balance between the two forms for optimal growth. The effects of nitrate and ammonium on gene expression, enzyme activity and metabolite composition have been documented extensively with the aim of understanding the way in which plant cells respond to the different forms of nitrogen, but ultimately the impact of these changes on the organisation and operation of the central metabolic network can only be addressed by analysing the fluxes supported by the network. Accordingly steady-state metabolic flux analysis was used to define the metabolic phenotype of a heterotrophic Arabidopsis thaliana cell culture grown in Murashige and Skoog and ammonium-free media, treatments that influenced growth and biomass composition. Fluxes through the central metabolic network were deduced from the redistribution of label into metabolic intermediates and end products observed when cells were labelled with [1-(13) C]-, [2-(13) C]- or [(13) C6 ]glucose, in tandem with (14) C-measurements of the net accumulation of biomass. Analysis of the flux maps showed that: (i) flux through the oxidative pentose phosphate pathway varied independently of the reductant demand for biosynthesis, (ii) non-plastidic processes made a significant and variable contribution to the provision of reducing power for the plastid, and (iii) the inclusion of ammonium in the growth medium increased cell maintenance costs, in agreement with the futile cycling model of ammonium toxicity. These conclusions highlight the complexity of the metabolic response to a change in nitrogen nutrition.

Carbon and nitrogen provisions alter the metabolic flux in developing soybean embryos

Soybean (Glycine max) seeds store significant amounts of their biomass as protein, levels of which reflect the carbon and nitrogen received by the developing embryo. The relationship between carbon and nitrogen supply during filling and seed composition was examined through a series of embryo-culturing experiments. Three distinct ratios of carbon to nitrogen supply were further explored through metabolic flux analysis. Labeling experiments utilizing [U-(13)C5]glutamine, [U-(13)C4]asparagine, and [1,2-(13)C2]glucose were performed to assess embryo metabolism under altered feeding conditions and to create corresponding flux maps. Additionally, [U-(14)C12]sucrose, [U-(14)C6]glucose, [U-(14)C5]glutamine, and [U-(14)C4]asparagine were used to monitor differences in carbon allocation. The analyses revealed that: (1) protein concentration as a percentage of total soybean embryo biomass coincided with the carbon-to-nitrogen ratio; (2) altered nitrogen supply did not dramatically impact relative amino acid or storage protein subunit profiles; and (3) glutamine supply contributed 10% to 23% of the carbon for biomass production, including 9% to 19% of carbon to fatty acid biosynthesis and 32% to 46% of carbon to amino acids. Seed metabolism accommodated different levels of protein biosynthesis while maintaining a consistent rate of dry weight accumulation. Flux through ATP-citrate lyase, combined with malic enzyme activity, contributed significantly to acetyl-coenzyme A production. These fluxes changed with plastidic pyruvate kinase to maintain a supply of pyruvate for amino and fatty acids. The flux maps were independently validated by nitrogen balancing and highlight the robustness of primary metabolism.

Metabolic network flux analysis for engineering plant systems

Metabolic network flux analysis (NFA) tools have proven themselves to be powerful aids to metabolic engineering of microbes by providing quantitative insights into the flows of material and energy through cellular systems. The development and application of NFA tools to plant systems has advanced in recent years and are yielding significant insights and testable predictions. Plants present substantial opportunities for the practical application of NFA but they also pose serious challenges related to the complexity of plant metabolic networks and to deficiencies in our knowledge of their structure and regulation. By considering the tools available and selected examples, this article attempts to assess where and how NFA is most likely to have a real impact on plant biotechnology.

Isotopically nonstationary 13C metabolic flux analysis

(13)C metabolic flux analysis (MFA) is a powerful approach for quantifying cell physiology based upon a combination of extracellular flux measurements and intracellular isotope labeling measurements. In this chapter, we present the method of isotopically nonstationary (13)C MFA (INST-MFA), which is applicable to systems that are at metabolic steady state, but are sampled during the transient period prior to achieving isotopic steady state following the introduction of a (13)C tracer. We describe protocols for performing the necessary isotope labeling experiments, for quenching and extraction of intracellular metabolites, for mass spectrometry (MS) analysis of metabolite labeling, and for computational flux estimation using INST-MFA. By combining several recently developed experimental and computational techniques, INST-MFA provides an important new platform for mapping carbon fluxes that is especially applicable to animal cell cultures, autotrophic organisms, industrial bioprocesses, high-throughput experiments, and other systems that are not amenable to steady-state (13)C MFA experiments.