Identification of hexose hydrolysis products in metabolic flux analytes: a case study of levulinic acid in plant protein hydrolysate

Concurrent isotope-assisted metabolic flux analysis and transcriptome profiling reveal responses of poplar cells to altered nitrogen and carbon supply

Reduced nitrogen is indispensable to plants. However, its limited availability in soil combined with the energetic and environmental impacts of nitrogen fertilizers motivates research into molecular mechanisms toward improving plant nitrogen use efficiency (NUE). We performed a systems-level investigation of this problem by employing multiple 'omics methodologies on cell suspensions of hybrid poplar (Populus tremula × Populus alba). Acclimation and growth of the cell suspensions in four nutrient regimes ranging from abundant to deficient supplies of carbon and nitrogen revealed that cell growth under low-nitrogen levels was associated with substantially higher NUE. To investigate the underlying metabolic and molecular mechanisms, we concurrently performed steady-state ¹³ C metabolic flux analysis with multiple isotope labels and transcriptomic profiling with cDNA microarrays. The ¹³ C flux analysis revealed that the absolute flux through the oxidative pentose phosphate pathway (oxPPP) was substantially lower (~threefold) under low-nitrogen conditions. Additionally, the flux partitioning ratio between the tricarboxylic acid cycle and anaplerotic pathways varied from 84%:16% under abundant carbon and nitrogen to 55%:45% under deficient carbon and nitrogen. Gene expression data, together with the flux results, suggested a plastidic localization of the oxPPP as well as transcriptional regulation of certain metabolic branchpoints, including those between glycolysis and the oxPPP. The transcriptome data also indicated that NUE-improving mechanisms may involve a redirection of excess carbon to aromatic metabolic pathways and extensive downregulation of potentially redundant genes (in these heterotrophic cells) that encode photosynthetic and light-harvesting proteins, suggesting the recruitment of these proteins as nitrogen sinks in nitrogen-abundant conditions.

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.

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.

Flux and reflux: metabolite reflux in plant suspension cells and its implications for isotope-assisted metabolic flux analysis

Isotope-assisted metabolic flux analysis (MFA) is a powerful methodology to quantify intracellular fluxes via isotope labeling experiments (ILEs). In batch cultures, which are often convenient, inexpensive or inevitable especially for eukaryotic systems, MFA is complicated by the presence of the initially present biomass. This unlabeled biomass may either mix with the newly synthesized labeled biomass or reflux into the metabolic network, thus masking the true labeling patterns in the newly synthesized biomass. Here, we report a detailed investigation of such metabolite reflux in cell suspensions of the tree poplar. In ILEs supplying 28% or 98% U-(13)C glucose as the sole organic carbon source, biomass components exhibited lower (13)C enrichments than the supplied glucose as well as anomalous isotopomers not explainable by simple mixing of the initial and newly synthesized biomass. These anomalous labeling patterns were most prominent in a 98% U-(13)C glucose ILE. By comparing the performance of light- and dark-grown cells as well as by analyzing the isotope labeling patterns in aspartic and glutamic acids, we eliminated photosynthetic or anaplerotic fixation of extracellular (12)CO2 as explanations for the anomalous labeling patterns. We further investigated four different metabolic models for interpreting the labeling patterns and evaluating fluxes: (i) a carbon source (glucose) dilution model, (ii) an isotopomer correction model with uniform dilution for all amino acids, (iii) an isotopomer correction model with variable dilution for different amino acids, and (iv) a comprehensive metabolite reflux model. Of these, the metabolite reflux model provided a substantially better fit for the observed labeling patterns (sum of squared residues: 538) than the other three models whose sum of squared residues were (i) 4626, (ii) 4983, and (iii) 1748, respectively. We compared fluxes determined using the metabolite reflux model to those determined using an independent methodology involving an excessively long ILE to wash out initial biomass and a minimal reflux model. This comparison showed identical or similar distributions for a majority of fluxes, thus validating our comprehensive reflux model. In summary, we have demonstrated the need for quantifying interactions between initially present biomass and newly synthesized biomass in batch ILEs, especially through the use of ≈100% U-(13)C carbon sources. Our ILEs reveal a high amount of metabolite reflux in poplar cell suspensions, which is well explained by a comprehensive metabolite reflux model.

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.

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.

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.

Analysis of proteinogenic amino acid and starch labeling by 2D NMR

Comprehensive analysis of isotopic labeling patterns of metabolites in proteinogenic amino acids and starch for plant systems lay in the powerful tool of 2-Dimensional [(1)H, (13)C] Nuclear Magnetic Resonance (2D NMR) spectroscopy. From (13)C-labeling experiments, 2D NMR provides information on the labeling of particular carbon positions, which contributes to the quantification of positional isotope isomers (isotopomer). 2D Heteronuclear Single Quantum Correlation (HSQC) NMR distinguishes particularly between the labeling patterns of adjacent carbon atoms, and leads to a characteristic enrichment of each carbon atom of amino acids and glucosyl and mannosyl units present in hydrolysates of glycosylated protein. Furthermore, this technique can quantitatively classify differences in glucosyl units of starch hydrolysate and of protein hydrolysate of plant biomass. Therefore, the 2D HSQC NMR method uses proteinogenic amino acids and starch to provide an understanding of carbon distribution of compartmentalization in the plant system. NMR has the advantage of minimal sample handle without separate individual compounds prior to analysis, for example multiple isotopomers can be detected, and their distribution extracted quantitatively from a single 2D HSQC NMR spectrum. The peak structure obtained from the HSQC experiment show multiplet patterns, which are directly related to isotopomer balancing. These abundances can be translated to maximum information on the metabolic flux analysis. Detailed methods for the extractions of protein, oil, soluble sugars, and starch, hydrolysis of proteinogenic amino acid and starch, and NMR preparation using soybean embryos cultured in vitro as a model plant systems are reported in this text. In addition, this chapter includes procedures to obtain the relative intensity of 16 amino acids and glucosyl units from protein hydrolysate and the glucosyl units of starch hydrolysate of soybean embryos in 2D HSQC NMR spectra.

Evidence for extensive heterotrophic metabolism, antioxidant action, and associated regulatory events during winter hardening in Sitka spruce

BACKGROUND

Cold acclimation in woody perennials is a metabolically intensive process, but coincides with environmental conditions that are not conducive to the generation of energy through photosynthesis. While the negative effects of low temperatures on the photosynthetic apparatus during winter have been well studied, less is known about how this is reflected at the level of gene and metabolite expression, nor how the plant generates primary metabolites needed for adaptive processes during autumn.

RESULTS

The MapMan tool revealed enrichment of the expression of genes related to mitochondrial function, antioxidant and associated regulatory activity, while changes in metabolite levels over the time course were consistent with the gene expression patterns observed. Genes related to thylakoid function were down-regulated as expected, with the exception of plastid targeted specific antioxidant gene products such as thylakoid-bound ascorbate peroxidase, components of the reactive oxygen species scavenging cycle, and the plastid terminal oxidase. In contrast, the conventional and alternative mitochondrial electron transport chains, the tricarboxylic acid cycle, and redox-associated proteins providing reactive oxygen species scavenging generated by electron transport chains functioning at low temperatures were all active.

CONCLUSIONS

A regulatory mechanism linking thylakoid-bound ascorbate peroxidase action with "chloroplast dormancy" is proposed. Most importantly, the energy and substrates required for the substantial metabolic remodeling that is a hallmark of freezing acclimation could be provided by heterotrophic metabolism.

Nuclear magnetic resonance methods for metabolic fluxomics

Fluxomics, through its core methodology of metabolic flux analysis (MFA), enables quantification of carbon traffic through cellular biochemical pathways. Isotope labeling experiments aid MFA by providing information on intracellular fluxes, especially through parallel and cyclic pathways. Nuclear magnetic resonance (NMR) and mass spectrometry (MS) are two complementary methods to measure abundances of isotopomers generated in these experiments. 2-D [(13)C, (1)H] heteronuclear correlation NMR spectra can detect (13)C isotopes coupled to protons and thus noninvasively separate molecules and atoms with a specific isotopic content from a mixture of molecular species. Furthermore, the fine structures of the peaks in these spectra can reveal scalar couplings between chemically bonded carbon atoms in the sample, from which isotopomer abundances can be quantified. This chapter introduces methods for NMR sample preparation and spectral acquisition of 2-D [(13)C, (1)H] correlation maps, followed by a detailed presentation of methods to process the spectra and quantify isotopomer abundances. We explain the use of the software NMRViewJ for spectral visualization and processing, as well as MATLAB scripts developed by us for peak extraction, deconvolution of overlapping peaklets, and isotopomer abundance quantification. Finally, we discuss the applications of NMR-derived isotopomer data toward quantitatively understanding metabolic pathways.

Isotope labelling of Rubisco subunits provides in vivo information on subcellular biosynthesis and exchange of amino acids between compartments

The architecture of plant metabolism includes substantial duplication of metabolite pools and enzyme catalyzed reactions in different subcellular compartments. This poses challenges for understanding the regulation of metabolism particularly in primary metabolism and amino acid biosynthesis. To explore the extent to which amino acids are made in single compartments and to gain insight into the metabolic precursors from which they derive, we used steady state (13) C labelling and analysed labelling in protein amino acids from plastid and cytosol. Ribulose 1,5-bisphosphate carboxylase/oxygenase (Rubisco) is a major component of green tissues and its large and small subunits are synthesized from different pools of amino acids in the plastid and cytosol, respectively. Developing Brassica napus embryos were cultured in the presence of [U-(13) C]-sucrose, [U-(13) C]-glucose, [U-(13) C]-glutamine or [U-(13) C]-alanine to generate proteins. The large subunits (LSU) and small subunits (SSU) of Rubisco were isolated and the labelling in their constituent amino acids was analysed by gas chromatography-mass spectrometry. Amino acids including alanine, glycine and serine exhibited different (13) C enrichment in the LSU and SSU, demonstrating that these pools have different metabolic origins and are not isotopically equilibrated between the plastid and cytosol on the time scale of cellular growth. Potential extensions of this novel approach to other macromolecules, organelles and cell types of eukaryotes are discussed.

Metabolic cartography: experimental quantification of metabolic fluxes from isotopic labelling studies

For the past decade, flux maps have provided researchers with an in-depth perspective on plant metabolism. As a rapidly developing field, significant headway has been made recently in computation, experimentation, and overall understanding of metabolic flux analysis. These advances are particularly applicable to the study of plant metabolism. New dynamic computational methods such as non-stationary metabolic flux analysis are finding their place in the toolbox of metabolic engineering, allowing more organisms to be studied and decreasing the time necessary for experimentation, thereby opening new avenues by which to explore the vast diversity of plant metabolism. Also, improved methods of metabolite detection and measurement have been developed, enabling increasingly greater resolution of flux measurements and the analysis of a greater number of the multitude of plant metabolic pathways. Methods to deconvolute organelle-specific metabolism are employed with increasing effectiveness, elucidating the compartmental specificity inherent in plant metabolism. Advances in metabolite measurements have also enabled new types of experiments, such as the calculation of metabolic fluxes based on (13)CO(2) dynamic labelling data, and will continue to direct plant metabolic engineering. Newly calculated metabolic flux maps reveal surprising and useful information about plant metabolism, guiding future genetic engineering of crops to higher yields. Due to the significant level of complexity in plants, these methods in combination with other systems biology measurements are necessary to guide plant metabolic engineering in the future.

Metabolic flux analysis in plants: coping with complexity

Theory and experience in metabolic engineering both show that metabolism operates at the network level. In plants, this complexity is compounded by a high degree of compartmentation and the synthesis of a very wide array of secondary metabolic products. A further challenge to understanding and predicting plant metabolic function is posed by our ignorance about the structure of metabolic networks even in well-studied systems. Metabolic flux analysis (MFA) provides tools to measure and model the functioning of metabolism, and is making significant contributions to coping with their complexity. This review gives an overview of different MFA approaches, the measurements required to implement them and the information they yield. The application of MFA methods to plant systems is then illustrated by several examples from the recent literature. Next, the challenges that plant metabolism poses for MFA are discussed together with ways that these can be addressed. Lastly, new developments in MFA are described that can be expected to improve the range and reliability of plant MFA in the coming years.

Metabolic flux maps comparing the effect of temperature on protein and oil biosynthesis in developing soybean cotyledons

Metabolic flux maps developed from 13C metabolic flux analysis (13C MFA) are effective tools for assessing the response of biological systems to genetic or environmental perturbations, and for identifying possible metabolic engineering targets. Experimental treatments were designed to distinguish between temperature effects prior to, and during incubation in vitro, on primary metabolism in developing soybeans. Biomass accumulation increased with temperature as did carbon partitioning into lipids. The flux through the plastidic oxidative pentose phosphate pathway (pgl(P)) relative to sucrose intake remained fairly constant [ approximately 56% (+/-24%)] when cotyledons were transferred from an optimum growth temperature to varying temperatures in in vitro culture, signifying a rigid node under these conditions. However, pgl(P) flux ranged from 57 to 77% of sucrose intake when growth temperature in planta varied and were cultured in vitro at the same temperature (as the plant), indicating a flexible node for this case. The carbon flux through the anaplerotic reactions catalysed by plastidic malic enzyme (me(P)), cytosolic phosphoenolpyruvate (PEP) carboxylase and the malate (Mal) transporter from the cytosol to mitochondrion varied dramatically with temperature and had a direct influence on the carbon partitioning into protein and oil from the plastidic pyruvate (Pyr) pool. These results of the in vitro culture indicate that temperature during early stages of development has a dominant effect on establishing capacity for flux through certain components of central carbon metabolism.