NMR-based fluxomics: quantitative 2D NMR methods for isotopomers analysis

Practical Aspects of NMR-Based Metabolomics

While NMR-based metabolomics is only about 20 years old, NMR has been a key part of metabolic and metabolism studies for >40 years. Historically, metabolic researchers used NMR because of its high level of reproducibility, superb instrument stability, facile sample preparation protocols, inherently quantitative character, non-destructive nature, and amenability to automation. In this chapter, we provide a short history of NMR-based metabolomics. We then provide a detailed description of some of the practical aspects of performing NMR-based metabolomics studies including sample preparation, pulse sequence selection, and spectral acquisition and processing. The two different approaches to metabolomics data analysis, targeted vs. untargeted, are briefly outlined. We also describe several software packages to help users process NMR spectra obtained via these two different approaches. We then give several examples of useful or interesting applications of NMR-based metabolomics, ranging from applications to drug toxicology, to identifying inborn errors of metabolism to analyzing the contents of biofluids from dairy cattle. Throughout this chapter, we will highlight the strengths and limitations of NMR-based metabolomics. Additionally, we will conclude with descriptions of recent advances in NMR hardware, methodology, and software and speculate about where NMR-based metabolomics is going in the next 5-10 years.

GC/MS-based 13C metabolic flux analysis resolves the parallel and cyclic photomixotrophic metabolism of Synechocystis sp. PCC 6803 and selected deletion mutants including the Entner-Doudoroff and phosphoketolase pathways

BACKGROUND

Cyanobacteria receive huge interest as green catalysts. While exploiting energy from sunlight, they co-utilize sugar and CO₂. This photomixotrophic mode enables fast growth and high cell densities, opening perspectives for sustainable biomanufacturing. The model cyanobacterium Synechocystis sp. PCC 6803 possesses a complex architecture of glycolytic routes for glucose breakdown that are intertwined with the CO₂-fixing Calvin-Benson-Bassham (CBB) cycle. To date, the contribution of these pathways to photomixotrophic metabolism has remained unclear.

RESULTS

Here, we developed a comprehensive approach for ¹³C metabolic flux analysis of Synechocystis sp. PCC 6803 during steady state photomixotrophic growth. Under these conditions, the Entner-Doudoroff (ED) and phosphoketolase (PK) pathways were found inactive but the microbe used the phosphoglucoisomerase (PGI) (63.1%) and the oxidative pentose phosphate pathway (OPP) shunts (9.3%) to fuel the CBB cycle. Mutants that lacked the ED pathway, the PK pathway, or phosphofructokinases were not affected in growth under metabolic steady-state. An ED pathway-deficient mutant (Δeda) exhibited an enhanced CBB cycle flux and increased glycogen formation, while the OPP shunt was almost inactive (1.3%). Under fluctuating light, ∆eda showed a growth defect, different to wild type and the other deletion strains.

CONCLUSIONS

The developed approach, based on parallel ¹³C tracer studies with GC-MS analysis of amino acids, sugars, and sugar derivatives, optionally adding NMR data from amino acids, is valuable to study fluxes in photomixotrophic microbes to detail. In photomixotrophic cells, PGI and OPP form glycolytic shunts that merge at switch points and result in synergistic fueling of the CBB cycle for maximized CO₂ fixation. However, redirected fluxes in an ED shunt-deficient mutant and the impossibility to delete this shunt in a GAPDH2 knockout mutant, indicate that either minor fluxes (below the resolution limit of ¹³C flux analysis) might exist that could provide catalytic amounts of regulatory intermediates or alternatively, that EDA possesses additional so far unknown functions. These ideas require further experiments.

Rapid quantitative 1H–13C two-dimensional NMR with high precision

Two dimensional (2D) ¹H–¹³C heteronuclear single-quantum correlation (HSQC) spectroscopy has recently been proposed for quantitative determination of typical linear low density polyethylene (LLDPE) with high accuracy. It requires highly precise measurement to achieve further reliable quantification. In this context, this paper aims at determining conditions that allow the achievement of high precision. On the basis of the optimized parameters, two time-saving strategies, nonuniform sampling (NUS) and band-selective HSQC are evaluated on model polyolefins in terms of repeatability. Precision better than 0.3% and 5% for ethylene content (E mol%) and 1-hexene content (H mol%) of the model poly(ethylene-co-1-hexene)s are obtained with 50% NUS or band-selective HSQC. Moreover, dramatic precision enhancements can be achieved with the combination of band-selective HSQC and 50% NUS, in which repeatabilities better than 0.15% and 2.5% for E mol% and H mol% are observed. The experiment times are reduced to about 0.5 h. These methods open important perspectives for rapid, precise and accurate quantitative analysis of complex polymers.

Precision better than 2.5% can be achieved with the combination of band-selective HSQC and 50% NUS in 0.5 h.

Nuclear Magnetic Resonance Spectroscopy in Clinical Metabolomics and Personalized Medicine: Current Challenges and Perspectives

Personalized medicine is probably the most promising area being developed in modern medicine. This approach attempts to optimize the therapies and the patient care based on the individual patient characteristics. Its success highly depends on the way the characterization of the disease and its evolution, the patient’s classification, its follow-up and the treatment could be optimized. Thus, personalized medicine must combine innovative tools to measure, integrate and model data. Towards this goal, clinical metabolomics appears as ideally suited to obtain relevant information. Indeed, the metabolomics signature brings crucial insight to stratify patients according to their responses to a pathology and/or a treatment, to provide prognostic and diagnostic biomarkers, and to improve therapeutic outcomes. However, the translation of metabolomics from laboratory studies to clinical practice remains a subsequent challenge. Nuclear magnetic resonance spectroscopy (NMR) and mass spectrometry (MS) are the two key platforms for the measurement of the metabolome. NMR has several advantages and features that are essential in clinical metabolomics. Indeed, NMR spectroscopy is inherently very robust, reproducible, unbiased, quantitative, informative at the structural molecular level, requires little sample preparation and reduced data processing. NMR is also well adapted to the measurement of large cohorts, to multi-sites and to longitudinal studies. This review focus on the potential of NMR in the context of clinical metabolomics and personalized medicine. Starting with the current status of NMR-based metabolomics at the clinical level and highlighting its strengths, weaknesses and challenges, this article also explores how, far from the initial “opposition” or “competition”, NMR and MS have been integrated and have demonstrated a great complementarity, in terms of sample classification and biomarker identification. Finally, a perspective discussion provides insight into the current methodological developments that could significantly raise NMR as a more resolutive, sensitive and accessible tool for clinical applications and point-of-care diagnosis. Thanks to these advances, NMR has a strong potential to join the other analytical tools currently used in clinical settings.

IsoSolve: An Integrative Framework to Improve Isotopic Coverage and Consolidate Isotopic Measurements by Mass Spectrometry and/or Nuclear Magnetic Resonance

Stable-isotope labeling experiments are widely used to investigate the topology and functioning of metabolic networks. Label incorporation into metabolites can be quantified using a broad range of mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy methods, but in general, no single approach can completely cover isotopic space, even for small metabolites. The number of quantifiable isotopic species could be increased and the coverage of isotopic space improved by integrating measurements obtained by different methods; however, this approach has remained largely unexplored because no framework able to deal with partial, heterogeneous isotopic measurements has yet been developed. Here, we present a generic computational framework based on symbolic calculus that can integrate any isotopic data set by connecting measurements to the chemical structure of the molecules. As a test case, we apply this framework to isotopic analyses of amino acids, which are ubiquitous to life, central to many biological questions, and can be analyzed by a broad range of MS and NMR methods. We demonstrate how this integrative framework helps to (i) clarify and improve the coverage of isotopic space, (ii) evaluate the complementarity and redundancy of different techniques, (iii) consolidate isotopic data sets, (iv) design experiments, and (v) guide future analytical developments. This framework, which can be applied to any labeled element, isotopic tracer, metabolite, and analytical platform, has been implemented in IsoSolve (available at https://github.com/MetaSys-LISBP/IsoSolve and https://pypi.org/project/IsoSolve), an open-source software that can be readily integrated into data analysis pipelines.

Optimised collection of non-uniformly sampled 2D-HSQC NMR spectra for use in metabolic flux analysis

Nuclear magnetic resonance (NMR) spectroscopy is integral to metabolic studies; yet, it can suffer from the long acquisition times required to collect data of sufficient signal strength and resolution. The use of non-uniform sampling (NUS) allows faster collection of NMR spectra without loss of spectral integrity. When planning experimental methodologies to perform metabolic flux analysis (MFA) of cell metabolism, a variety of options are available for the acquisition of NUS NMR data. Before beginning data collection, decisions have to be made regarding selection of pulse sequence, number of transients and NUS specific parameters such as the sampling level and sampling schedule. Poor choices will impact data quality, which may have a negative effect on the subsequent analysis and biological interpretation. Herein, we describe factors that should be considered when setting up non-uniformly sampled 2D-¹ H,¹³ C HSQC NMR experiments for MFA and provide a standard protocol for users to follow.

Charting the Metabolic Landscape of the Facultative Methylotroph Bacillus methanolicus

Methanol is inexpensive, is easy to transport, and can be produced both from renewable and from fossil resources without mobilizing arable lands. As such, it is regarded as a potential carbon source to transition toward a greener industrial chemistry. Metabolic engineering of bacteria and yeast able to efficiently consume methanol is expected to provide cell factories that will transform methanol into higher-value chemicals in the so-called methanol economy. Toward that goal, the study of natural methylotrophs such as Bacillus methanolicus is critical to understand the origin of their efficient methylotrophy. This knowledge will then be leveraged to transform such natural strains into new cell factories or to design methylotrophic capability in other strains already used by the industry.

Bacillus methanolicus MGA3 is a thermotolerant and relatively fast-growing methylotroph able to secrete large quantities of glutamate and lysine. These natural characteristics make B. methanolicus a good candidate to become a new industrial chassis organism, especially in a methanol-based economy. Intriguingly, the only substrates known to support B. methanolicus growth as sole sources of carbon and energy are methanol, mannitol, and, to a lesser extent, glucose and arabitol. Because fluxomics provides the most direct readout of the cellular phenotype, we hypothesized that comparing methylotrophic and nonmethylotrophic metabolic states at the flux level would yield new insights into MGA3 metabolism. In this study, we designed and performed a ¹³C metabolic flux analysis (¹³C-MFA) of the facultative methylotroph B. methanolicus MGA3 growing on methanol, mannitol, and arabitol to compare the associated metabolic states. On methanol, results showed a greater flux in the ribulose monophosphate (RuMP) pathway than in the tricarboxylic acid (TCA) cycle, thus validating previous findings on the methylotrophy of B. methanolicus. New insights related to the utilization of cyclic RuMP versus linear dissimilation pathways and between the RuMP variants were generated. Importantly, we demonstrated that the linear detoxification pathways and the malic enzyme shared with the pentose phosphate pathway have an important role in cofactor regeneration. Finally, we identified, for the first time, the metabolic pathway used to assimilate arabitol. Overall, those data provide a better understanding of this strain under various environmental conditions.

IMPORTANCE Methanol is inexpensive, is easy to transport, and can be produced both from renewable and from fossil resources without mobilizing arable lands. As such, it is regarded as a potential carbon source to transition toward a greener industrial chemistry. Metabolic engineering of bacteria and yeast able to efficiently consume methanol is expected to provide cell factories that will transform methanol into higher-value chemicals in the so-called methanol economy. Toward that goal, the study of natural methylotrophs such as Bacillus methanolicus is critical to understand the origin of their efficient methylotrophy. This knowledge will then be leveraged to transform such natural strains into new cell factories or to design methylotrophic capability in other strains already used by the industry.

NMR-based metabolomics and fluxomics: developments and future prospects

Recent NMR developments are acting as game changers for metabolomics and fluxomics – a critical and perspective review.

Rapid two-dimensional ALSOFAST-HSQC experiment for metabolomics and fluxomics studies: application to a 13C-enriched cancer cell model treated with gold nanoparticles

Isotope labeling enables the use of ¹³C-based metabolomics techniques with strongly improved resolution for a better identification of relevant metabolites and tracing of metabolic fluxes in cell and animal models, as required in fluxomics studies. However, even at high NMR-active isotope abundance, the acquisition of one-dimensional ¹³C and classical two-dimensional ¹H,¹³C-HSQC experiments remains time consuming. With the aim to provide a shorter, more efficient alternative, herein we explored the ALSOFAST-HSQC experiment with its rapid acquisition scheme for the analysis of ¹³C-labeled metabolites in complex biological mixtures. As an initial step, the parameters of the pulse sequence were optimized to take into account the specific characteristics of the complex samples. We then applied the fast two-dimensional experiment to study the effect of different kinds of antioxidant gold nanoparticles on a HeLa cancer cell model grown on ¹³C glucose-enriched medium. As a result, ¹H,¹³C-2D correlations could be obtained in a couple of seconds to few minutes, allowing a simple and reliable identification of various ¹³C-enriched metabolites and the determination of specific variations between the different sample groups. Thus, it was possible to monitor glucose metabolism in the cell model and study the antioxidant effect of the coated gold nanoparticles in detail. Finally, with an experiment time of only half an hour, highly resolved ¹H,¹³C-HSQC spectra using the ALSOFAST-HSQC pulse sequence were acquired, revealing the isotope-position-patterns of the corresponding ¹³C-nuclei from carbon multiplets. Graphical abstract Fast NMR applied to metabolomics and fluxomics studies with gold nanoparticles.

High-throughput quantification of the levels and labeling abundance of free amino acids by liquid chromatography tandem mass spectrometry

Accurate assessment of mass isotopomer distributions (MIDs) of intracellular metabolites, such as free amino acids (AAs), is crucial for quantifying in vivo fluxes. To date, the majority of studies that measured AA MIDs have relied on the analysis of proteinogenic rather than free AAs by: i) GC-MS, which involved cumbersome process of derivatization, or ii) NMR, which requires large quantities of biological sample. In this work, the development and validation of a high-throughput LC-MS/MS method allowing the quantification of the levels and labeling of free AAs is described. Sensitivity in the order of the femtomol was achieved using multiple reaction monitoring mode (MRM). The MIDs of all free AAs were assessed without the need of derivatization, and were validated (except for Trp) on a mixture of unlabeled AA standards. Finally, this method was applied to the determination of the ¹³C-labeling abundance in free AAs extracted from maize embryos cultured with ¹³C-glutamine or ¹³C-glucose. Although Cys was below the limit of detection in these biological samples, the MIDs of a total of 18 free AAs were successfully determined. Due to the increased application of tandem mass spectrometry for ¹³C-Metabolic Flux Analysis, this novel method will enable the assessment of more complete and accurate labeling information of intracellular AAs, and therefore a better definition of the fluxes.

Multilevel interaction of the DnaK/DnaJ(HSP70/HSP40) stress-responsive chaperone machine with the central metabolism

Networks of molecular chaperones maintain cellular protein homeostasis by acting at nearly every step in the biogenesis of proteins and protein complexes. Herein, we demonstrate that the major chaperone DnaK/HSP70 of the model bacterium Escherichia coli is critical for the proper functioning of the central metabolism and for the cellular response to carbon nutrition changes, either directly or indirectly via the control of the heat-shock response. We identified carbon sources whose utilization was positively or negatively affected by DnaK and isolated several central metabolism genes (among other genes identified in this work) that compensate for the lack of DnaK and/or DnaK/Trigger Factor chaperone functions in vivo. Using carbon sources with specific entry points coupled to NMR analyses of real-time carbon assimilation, metabolic coproducts production and flux rearrangements, we demonstrate that DnaK significantly impacts the hierarchical order of carbon sources utilization, the excretion of main coproducts and the distribution of metabolic fluxes, thus revealing a multilevel interaction of DnaK with the central metabolism.

Precise and rapid isotopomic analysis by (1)H-(13)C 2D NMR: Application to triacylglycerol matrices

An optimized HSQC sequence was tested and applied to triacylglycerol matrices to determine their isotopic and metabolomic profiles. Spectral aliasing and non-uniform sampling approaches were used to decrease the experimental time and to improve the resolution, respectively. An excellent long-term repeatability of signal integrals was achieved enabling to perform isotopic measurements. Thirty-two commercial vegetable oils were analyzed by this methodology. The results show that this method can be used to classify oil samples according to their geographical and botanical origins.

Impact of kinetic isotope effects in isotopic studies of metabolic systems

Background

Isotope labeling experiments (ILEs) are increasingly used to investigate the functioning of metabolic systems. Some enzymes are subject to kinetic isotope effects (KIEs) which modulate reaction rates depending on the isotopic composition of their substrate(s). KIEs may therefore affect both the propagation of isotopes through metabolic networks and their operation, and ultimately jeopardize the biological value of ILEs. However, the actual impact of KIEs on metabolism has never been investigated at the system level.

Results

First, we developed a framework which integrates KIEs into kinetic and isotopic models of metabolism, thereby accounting for their system-wide effects on metabolite concentrations, metabolic fluxes, and isotopic patterns. Then, we applied this framework to assess the impact of KIEs on the central carbon metabolism of Escherichia coli in the context of ¹³C-ILEs, under different situations commonly encountered in laboratories. Results showed that the impact of KIEs strongly depends on the label input and on the variable considered but is significantly lower than expected intuitively from measurements on isolated enzymes. The global robustness of both the metabolic operation and isotopic patterns largely emerge from intrinsic properties of metabolic networks, such as the distribution of control across the network and bidirectional isotope exchange.

Conclusions

These results demonstrate the necessity of investigating the impact of KIEs at the level of the entire system, contradict previous hypotheses that KIEs would have a strong effect on isotopic distributions and on flux determination, and strengthen the biological value of ¹³C-ILEs. The proposed modeling framework is generic and can be used to investigate the impact of all the isotopic tracers (²H, ¹³C, ¹⁵N, ¹⁸O, etc.) on different isotopic datasets and metabolic systems. By allowing the integration of isotopic and metabolomics data collected under stationary and/or non-stationary conditions, it may also assist interpretations of ILEs and facilitate the development of more accurate kinetic models with improved explicative and predictive capabilities.

Electronic supplementary material

The online version of this article (doi:10.1186/s12918-015-0213-8) contains supplementary material, which is available to authorized users.

White biotechnology: State of the art strategies for the development of biocatalysts for biorefining

White biotechnology is a term that is now often used to describe the implementation of biotechnology in the industrial sphere. Biocatalysts (enzymes and microorganisms) are the key tools of white biotechnology, which is considered to be one of the key technological drivers for the growing bioeconomy. Biocatalysts are already present in sectors such as the chemical and agro-food industries, and are used to manufacture products as diverse as antibiotics, paper pulp, bread or advanced polymers. This review proposes an original and global overview of highly complementary fields of biotechnology at both enzyme and microorganism level. A certain number of state of the art approaches that are now being used to improve the industrial fitness of biocatalysts particularly focused on the biorefinery sector are presented. The first part deals with the technologies that underpin the development of industrial biocatalysts, notably the discovery of new enzymes and enzyme improvement using directed evolution techniques. The second part describes the toolbox available by the cell engineer to shape the metabolism of microorganisms. And finally the last part focuses on the 'omic' technologies that are vital for understanding and guide microbial engineering toward more efficient microbial biocatalysts. Altogether, these techniques and strategies will undoubtedly help to achieve the challenging task of developing consolidated bioprocessing (i.e. CBP) readily available for industrial purpose.

Hyperpolarized NMR of plant and cancer cell extracts at natural abundance

Natural abundance ¹³C 1D and 2D NMR spectra of biological extracts are recorded in a single scan for samples hyperpolarised by dissolution dynamic nuclear polarization combined with cross polarization.

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.

Sampling of intracellular metabolites for stationary and non-stationary (13)C metabolic flux analysis in Escherichia coli

The analysis of metabolic intermediates is a rich source of isotopic information for (13)C metabolic flux analysis ((13)C-MFA) and extends the range of its applications. The sampling of labeled metabolic intermediates is particularly important to obtain reliable isotopic information. The assessment of the different sampling procedures commonly used to generate such data, therefore, is crucial. In this work, we thoroughly evaluated several sampling procedures for stationary and non-stationary (13)C-MFA using Escherichia coli. We first analyzed the efficiency of these procedures for quenching metabolism and found that procedures based on cold or boiling solvents are reliable, in contrast to fast filtration, which is not. We also showed that separating the cells from the broth is not necessary in isotopic stationary state conditions. On the other hand, we demonstrated that the presence of metabolic intermediates outside the cells strongly affects the transient isotopic data monitored during non-stationary (13)C-labeling experiments. Meaningful isotopic data can be obtained by recovering intracellular labeled metabolites from pellets of cells centrifuged in cold solvent. We showed that if the intracellular pools are not separated from the extracellular ones, accurate flux maps can be established provided that the contribution of exogenous compounds is taken into account in the metabolic flux model.

A novel platform for automated high-throughput fluxome profiling of metabolic variants

Advances in metabolic engineering are enabling the creation of a large number of cell factories. However, high-throughput platforms do not yet exist for rapidly analyzing the metabolic network of the engineered cells. To fill the gap, we developed an integrated solution for fluxome profiling of large sets of biological systems and conditions. This platform combines a robotic system for (13)C-labelling experiments and sampling of labelled material with NMR-based isotopic fingerprinting and automated data interpretation. As a proof-of-concept, this workflow was applied to discriminate between Escherichia coli mutants with gradual expression of the glucose-6-phosphate dehydrogenase. Metabolic variants were clearly discriminated while pathways that support metabolic flexibility towards modulation of a single enzyme were elucidating. By directly connecting the data flow between cell cultivation and flux quantification, considerable advances in throughput, robustness, release of resources and screening capacity were achieved. This will undoubtedly facilitate the development of efficient cell factories.

Quantitative 2D liquid-state NMR

Two-dimensional (2D) liquid-state NMR has a very high potential to simultaneously determine the absolute concentration of small molecules in complex mixtures, thanks to its capacity to separate overlapping resonances. However, it suffers from two main drawbacks that probably explain its relatively late development. First, the 2D NMR signal is strongly molecule-dependent and site-dependent; second, the long duration of 2D NMR experiments prevents its general use for high-throughput quantitative applications and affects its quantitative performance. Fortunately, the last 10 years has witnessed an increasing number of contributions where quantitative approaches based on 2D NMR were developed and applied to solve real analytical issues. This review aims at presenting these recent efforts to reach a high trueness and precision in quantitative measurements by 2D NMR. After highlighting the interest of 2D NMR for quantitative analysis, the different strategies to determine the absolute concentrations from 2D NMR spectra are described and illustrated by recent applications. The last part of the manuscript concerns the recent development of fast quantitative 2D NMR approaches, aiming at reducing the experiment duration while preserving - or even increasing - the analytical performance. We hope that this comprehensive review will help readers to apprehend the current landscape of quantitative 2D NMR, as well as the perspectives that may arise from it.

Labelling analysis for ¹³C MFA using NMR spectroscopy

NMR spectroscopy is an efficient method for analyzing (13)C labelling of cellular metabolites. The strength of it is especially the ability to provide direct quantitative positional information on the (13)C labelling status of carbon atoms in metabolites. NMR spectroscopic methods allow also for detection of contiguously (13)C-labelled fragments in the carbon backbones of the metabolites. Furthermore, the recent developments of NMR spectroscopy hardware have substantially improved the sensitivity of the methods. In this chapter we describe a method for analyzing the (13)C labelling of the biomass amino acids for metabolic flux analysis, sample preparation for NMR spectroscopy, acquiring and processing the NMR spectra, and extracting the (13)C labelling information from the NMR data. Different NMR methods are applied depending on the (13)C labelling strategy chosen. These strategies include uniform (13)C labelling, positional (13)C labelling, or a combination of both. Not only the preparation of sample for analysis of (13)C labelling in proteinogenic amino acids in biomass is described, but also the necessary modifications to the method when analysis of (13)C labelling in free metabolic intermediates is of interest. Finally the strategies for using the different NMR-detected (13)C labelling data in (13)C MFA are discussed.

Customization of ¹³C-MFA strategy according to cell culture system

(13)C-MFA is far from being a simple assay for quantifying metabolic activity. It requires considerable up-front experimental planning and familiarity with the cell culture system in question, as well as optimized analytics and adequate computation frameworks. The success of a (13)C-MFA experiment is ultimately rated by the ability to accurately quantify the flux of one or more reactions of interest. In this chapter, we describe the different (13)C-MFA strategies that have been developed for the various fermentation or cell culture systems, as well as the limitations of the respective strategies. The strategies are affected by many factors and the (13)C-MFA modeling and experimental strategy must be tailored to conditions. The prevailing philosophy in the computation process is that any metabolic processes that produce significant systematic bias in the labeling pattern of the metabolites being measured must be described in the model. It is equally important to plan a labeling strategy by analytical screening or by heuristics.

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.

Ultrafast 2D NMR: an emerging tool in analytical spectroscopy

Two-dimensional nuclear magnetic resonance (2D NMR) spectroscopy is widely used in chemical and biochemical analyses. Multidimensional NMR is also witnessing increased use in quantitative and metabolic screening applications. Conventional 2D NMR experiments, however, are affected by inherently long acquisition durations, arising from their need to sample the frequencies involved along their indirect domains in an incremented, scan-by-scan nature. A decade ago, a so-called ultrafast (UF) approach was proposed, capable of delivering arbitrary 2D NMR spectra involving any kind of homo- or heteronuclear correlation, in a single scan. During the intervening years, the performance of this subsecond 2D NMR methodology has been greatly improved, and UF 2D NMR is rapidly becoming a powerful analytical tool experiencing an expanded scope of applications. This review summarizes the principles and main developments that have contributed to the success of this approach and focuses on applications that have been recently demonstrated in various areas of analytical chemistry--from the real-time monitoring of chemical and biochemical processes, to extensions in hyphenated techniques and in quantitative applications.

IsoDesign: a software for optimizing the design of 13C-metabolic flux analysis experiments

The growing demand for (13) C-metabolic flux analysis ((13) C-MFA) in the field of metabolic engineering and systems biology is driving the need to rationalize expensive and time-consuming (13) C-labeling experiments. Experimental design is a key step in improving both the number of fluxes that can be calculated from a set of isotopic data and the precision of flux values. We present IsoDesign, a software that enables these parameters to be maximized by optimizing the isotopic composition of the label input. It can be applied to (13) C-MFA investigations using a broad panel of analytical tools (MS, MS/MS, (1) H NMR, (13) C NMR, etc.) individually or in combination. It includes a visualization module to intuitively select the optimal label input depending on the biological question to be addressed. Applications of IsoDesign are described, with an example of the entire (13) C-MFA workflow from the experimental design to the flux map including important practical considerations. IsoDesign makes the experimental design of (13) C-MFA experiments more accessible to a wider biological community. IsoDesign is distributed under an open source license at http://metasys.insa-toulouse.fr/software/isodes/

The carbon storage regulator (Csr) system exerts a nutrient-specific control over central metabolism in Escherichia coli strain Nissle 1917

The role of the post-transcriptional carbon storage regulator (Csr) system in nutrient utilization and in the control of the central metabolism in E. coli reference commensal strain Nissle 1917 was investigated. Analysis of the growth capabilities of mutants altered for various components of the Csr system (csrA51, csrB, csrC and csrD mutations) showed that only the protein CsrA - the key component of the system - exerts a marked role in carbon nutrition. Attenuation of CsrA activity in the csrA51 mutant affects the growth efficiency on a broad range of physiologically relevant carbon sources, including compounds utilized by the Entner-Doudoroff (ED) pathway. Detailed investigations of the metabolomes and fluxomes of mutants and wild-type cells grown on carbon sources representative of glycolysis and of the ED pathway (glucose and gluconate, respectively), revealed significant re-adjusting of central carbon metabolism for both compounds in the csrA51 mutant. However, the metabolic re-adjusting observed on gluconate was strikingly different from that observed on glucose, indicating a nutrient-specific control of metabolism by the Csr system.

Fast quantitative 1H-13C two-dimensional NMR with very high precision

Quantitative analysis by nuclear magnetic resonance (NMR) requires highly precise measurements to achieve reliable quantification. It is particularly true in (13)C site-specific natural isotope fractionation studied by nuclear magnetic resonance, where the range of values of (13)C isotopic deviations at natural abundance is highly restricted. Consequently, an NMR method capable of measuring δ(13)C ‰ values with a very high precision (a few per mil) is indispensable. This high degree of precision has already been achieved by one-dimensional (13)C acquisitions; however, this approach is limited by peak overlaps which reduce the precision of the isotope content determination, even for certain small molecules. It is therefore necessary to extend this promising methodology to a higher dimensionality. In this context, this paper aims at determining conditions that allow the achievement of two-dimensional (2D) (1)H-(13)C heteronuclear experiments with a precision of a few per mil in a reasonable time. Our results demonstrate that a high precision (repeatability of 2 per mil) can be reached with the (1)H-(13)C HSQC (Heteronuclear Single Quantum Correlation) experiment, thus satisfying the conditions needed to perform (13)C isotope analysis by 2D NMR. We also consider the impact of several approaches which have been proposed to reduce the duration of heteronuclear 2D experiments. Two of these common time-saving strategies, spectral aliasing and linear prediction, are fully compatible with the high-precision requirements of isotopic NMR, while a third one, nonuniform sampling, leads to dramatic precision losses. In conclusion, this study demonstrates the feasibility of very precise 2D NMR measurements and opens a number of application perspectives.

Ultrafast hetero-nuclear 2D J-resolved spectroscopy

Ultrafast techniques enable the acquisition of 2D NMR spectra in a single scan. In this study, we propose a new ultrafast experiment designed to record hetero-nuclear (1)H-(13)C J-resolved spectra in a fraction of a second. The approach is based on continuous constant-time phase modulated spatial encoding followed by a J-resolved detection scheme. An optional isotopic filter is implemented to remove the signal arising from (1)H bound to (12)C. While the most evident application of the technique proposed in this paper is the direct measurement of one bond scalar (13)C-(1)H couplings for structural elucidation purposes, it also offers interesting potentialities for measuring (13)C isotopic enrichments in metabolic samples. The main features of this methodology are presented, and the analytical performances of the ultrafast hetero-nuclear J-resolved pulse sequence are evaluated on model samples.

The ethylmalonyl-CoA pathway is used in place of the glyoxylate cycle by Methylobacterium extorquens AM1 during growth on acetate

Acetyl-CoA assimilation was extensively studied in organisms harboring the glyoxylate cycle. In this study, we analyzed the metabolism of the facultative methylotroph Methylobacterium extorquens AM1, which lacks isocitrate lyase, the key enzyme in the glyoxylate cycle, during growth on acetate. MS/MS-based proteomic analysis revealed that the protein repertoire of M. extorquens AM1 grown on acetate is similar to that of cells grown on methanol and includes enzymes of the ethylmalonyl-CoA (EMC) pathway that were recently shown to operate during growth on methanol. Dynamic 13C labeling experiments indicate the presence of distinct entry points for acetate: the EMC pathway and the TCA cycle. 13C steady-state metabolic flux analysis showed that oxidation of acetyl-CoA occurs predominantly via the TCA cycle and that assimilation occurs via the EMC pathway. Furthermore, acetyl-CoA condenses with the EMC pathway product glyoxylate, resulting in malate formation. The latter, also formed by the TCA cycle, is converted to phosphoglycerate by a reaction sequence that is reversed with respect to the serine cycle. Thus, the results obtained in this study reveal the utilization of common pathways during the growth of M. extorquens AM1 on C1 and C2 compounds, but with a major redirection of flux within the central metabolism. Furthermore, our results indicate that the metabolic flux distribution is highly complex in this model methylotroph during growth on acetate and is fundamentally different from organisms using the glyoxylate cycle.

Genome-scale reconstruction and system level investigation of the metabolic network of Methylobacterium extorquens AM1

Background

Methylotrophic microorganisms are playing a key role in biogeochemical processes - especially the global carbon cycle - and have gained interest for biotechnological purposes. Significant progress was made in the recent years in the biochemistry, genetics, genomics, and physiology of methylotrophic bacteria, showing that methylotrophy is much more widespread and versatile than initially assumed. Despite such progress, system-level description of the methylotrophic metabolism is currently lacking, and much remains to understand regarding the network-scale organization and properties of methylotrophy, and how the methylotrophic capacity emerges from this organization, especially in facultative organisms.

Results

In this work, we report on the integrated, system-level investigation of the metabolic network of the facultative methylotroph Methylobacterium extorquens AM1, a valuable model of methylotrophic bacteria. The genome-scale metabolic network of the bacterium was reconstructed and contains 1139 reactions and 977 metabolites. The sub-network operating upon methylotrophic growth was identified from both in silico and experimental investigations, and ¹³C-fluxomics was applied to measure the distribution of metabolic fluxes under such conditions. The core metabolism has a highly unusual topology, in which the unique enzymes that catalyse the key steps of C1 assimilation are tightly connected by several, large metabolic cycles (serine cycle, ethylmalonyl-CoA pathway, TCA cycle, anaplerotic processes). The entire set of reactions must operate as a unique process to achieve C1 assimilation, but was shown to be structurally fragile based on network analysis. This observation suggests that in nature a strong pressure of selection must exist to maintain the methylotrophic capability. Nevertheless, substantial substrate cycling could be measured within C2/C3/C4 inter-conversions, indicating that the metabolic network is highly versatile around a flexible backbone of central reactions that allows rapid switching to multi-carbon sources.

Conclusions

This work emphasizes that the metabolism of M. extorquens AM1 is adapted to its lifestyle not only in terms of enzymatic equipment, but also in terms of network-level structure and regulation. It suggests that the metabolism of the bacterium has evolved both structurally and functionally to an efficient but transitory utilization of methanol. Besides, this work provides a basis for metabolic engineering to convert methanol into value-added products.

Hyperpolarized (13)C spectroscopy and an NMR-compatible bioreactor system for the investigation of real-time cellular metabolism

The purpose of this study was to combine a three-dimensional NMR-compatible bioreactor with hyperpolarized (13)C NMR spectroscopy in order to probe cellular metabolism in real time. JM1 (immortalized rat hepatoma) cells were cultured in a three-dimensional NMR-compatible fluidized bioreactor. (31)P spectra were acquired before and after each injection of hyperpolarized [1-(13)C] pyruvate and subsequent (13)C spectroscopy at 11.7 T. (1)H and two-dimensional (1)H-(1)H-total correlation spectroscopy spectra were acquired from extracts of cells grown in uniformly labeled (13)C-glucose, on a 16.4 T, to determine (13)C fractional enrichment and distribution of (13)C label. JM1 cells were found to have a high rate of aerobic glycolysis in both two-dimensional culture and in the bioreactor, with 85% of the (13)C label from uniformly labeled (13)C-glucose being present as either lactate or alanine after 23 h. Flux measurements of pyruvate through lactate dehydrogenase and alanine aminotransferase in the bioreactor system were 12.18 +/- 0.49 nmols/sec/10(8) cells and 2.39 +/- 0.30 nmols/sec/10(8) cells, respectively, were reproducible in the same bioreactor, and were not significantly different over the course of 2 days. Although this preliminary study involved immortalized cells, this combination of technologies can be extended to the real-time metabolic exploration of primary benign and cancerous cells and tissues prior to and after therapy.

Exploring metabolomic approaches to analyse phospholipid biosynthetic pathways in Plasmodium

SUMMARYPlasmodium falciparum, the agent responsible for malaria, is an obligate intracellular protozoan parasite. For proliferation, differentiation and survival, it relies on its own protein-encoding genes, as well as its host cells for nutrient sources. Nutrients and subsequent metabolites are required by the parasites to support their high rate of growth and replication, particularly in the intra-erythrocytic stages of the parasite that are responsible for the clinical symptoms of the disease. Advances in mass spectrometry have improved the analysis of endogenous metabolites and enabled a global approach to identify the parasite's metabolites by the so-called metabolomic analyses. This level of analysis complements the genomic, transcriptomic and proteomic data already available and should allow the identification of novel metabolites, original pathways and networks of regulatory interactions within the parasite, and between the parasite and its hosts. The field of metabolomics is just in its infancy in P. falciparum, hence in this review, we concentrate on the available methodologies and their potential applications for deciphering important biochemical processes of the parasite, such as the astonishingly diverse phospholipid biosynthesis pathways. Elucidating the regulation of the biosynthesis of these crucial metabolites could help design of future anti-malarial drugs.

Demonstration of the ethylmalonyl-CoA pathway by using 13C metabolomics

The assimilation of one-carbon (C1) compounds, such as methanol, by serine cycle methylotrophs requires the continuous regeneration of glyoxylate. Instead of the glyoxylate cycle, this process is achieved by a not yet established pathway where CoA thioesters are known to play a key role. We applied state-of-the-art metabolomics and (13)C metabolomics strategies to demonstrate how glyoxylate is generated during methylotrophic growth in the isocitrate lyase-negative methylotroph Methylobacterium extorquens AM1. High-resolution mass spectrometry showed the presence of CoA thioesters specific to the recently proposed ethylmalonyl-CoA pathway. The operation of this pathway was demonstrated by short-term (13)C-labeling experiments, which allowed determination of the sequence of reactions from the order of label incorporation into the different CoA derivatives. Analysis of (13)C positional enrichment in glycine by NMR was consistent with the predicted labeling pattern as a result of the operation of the ethylmalonyl-CoA pathway and the unique operation of the latter for glyoxylate generation during growth on methanol. The results also revealed that 2 molecules of glyoxylate were regenerated in this process. This work provides a complete pathway for methanol assimilation in the model methylotroph M. extorquens AM1 and represents an important step toward the determination of the overall topology of its metabolic network. The operation of the ethylmalonyl-CoA pathway in M. extorquens AM1 has major implications for the physiology of these methylotrophs and their role in nature, and it also provides a common ground for C1 and C2 compound assimilation in isocitrate lyase-negative bacteria.

Impact of the salt stress on the photosynthetic carbon flux and 13C-label distribution within floridoside and digeneaside in Solieria chordalis

The flux of photosynthetic carbon used in the synthesis of low-molecular weight carbohydrates (digeneaside and floridoside) was investigated by (13)C and (1)H NMR spectroscopy in samples of the red seaweed, Solieria chordalis, incubated at different salinities (22, 34 and 50psu). Carbohydrates were labelled, by pulse-chase, with the stable isotope (13)C from NaH(13)CO(3). In vivo NMR analyses carried out with a cryogenic probe optimised for (13)C detection were performed directly on the living algal tissues to evidence the labelling of the carbohydrates with neither preliminary extraction nor purification step(s). The isotopic enrichment of each compound was determined by high-resolution (1)H and (13)C NMR spectroscopy. These analyses evidenced different orientations of the flux of the photosynthetic carbon in the algae according to the salt stress. At normal and low salinities, the photosynthetic carbon flux was responsible of 70% and 67% of the floridoside synthetized during the pulse period, respectively, whereas it was only of 30% in the thalli exposed to the high salinity, meaning a biosynthesis of high floridoside amount from endogen source leading to the osmotic regulation. Under normal and hyper-osmotic conditions, the stock of floridoside was used for cellular needs during the chase period, whereas it was not under hypo-osmotic conditions. The characterization of isotopomers composition of floridoside and digeneaside and the analysis of adjacent (13)C-labelling gives much more details on the effects of salinity on the metabolic pathways leading to the synthesis or the degradation of these molecules. High turnover of floridoside was evidenced at normal salinity during the chase period and products issued from the degradation of floridoside would not be used for the novo biosynthesis. That suggests that synthesis and degradation of floridoside may be realized in two different cellular compartments. The presence of more numerous (13)C-(13)C blocks in the carbon skeleton of the molecules from the up salt stressed thalli than in those from no salt stressed algae, concomitant with a slower degree of isotopic enrichment of the molecule, provided evidence that the two metabolic pathways (endogen and photosynthetic) may not share the precursor molecules involved in the floridoside synthesis and that these two routes may be totally separate until the constitution of floridoside molecule.

Spectral analysis of 1H coupled 13C spectra of the amino acids: adaptive spectral library of amino acid 13C isotopomers and positional fractional 13C enrichments

The natural abundance 1H-coupled 13C NMR spectra of all proteogenic amino acids were measured in D2O at pH* 1. The accurate 1H,13C spin-spin coupling constants were analyzed using total-line-shape fitting. The obtained spectral parameters can be used to establish a spectral library of amino acid 13C isotopomers. The adaptive spectral library principle is introduced and discussed in this article. The simulated spectra can be applied to quantification of 13C isotopomer mixtures of amino acids and, thus, for exploring metabolic pathways. Also a protocol for amino acid 13C isotopomer metabolomic profiling in 13C labeled glucose feeding experiments is outlined. The approach is suggested to give invaluable information about positional fractional 13C enrichments, which are not easily available by any other method.

Getting to grips with the plant metabolic network

Research into plant metabolism has a long history, and analytical approaches of ever-increasing breadth and sophistication have been brought to bear. We now have access to vast repositories of data concerning enzymology and regulatory features of enzymes, as well as large-scale datasets containing profiling information of transcripts, protein and metabolite levels. Nevertheless, despite this wealth of data, we remain some way off from being able to rationally engineer plant metabolism or even to predict metabolic responses. Within the past 18 months, rapid progress has been made, with several highly informative plant network interrogations being discussed in the literature. In the present review we will appraise the current state of the art regarding plant metabolic network analysis and attempt to outline what the necessary steps are in order to further our understanding of network regulation.