UFJCOSY: A Fast 3D NMR Method for Measuring Isotopic Enrichments in Complex Samples

CTCOSY-JRES: A high-resolution three-dimensional NMR method for unveiling J-couplings

Two-dimensional (2D) J-resolved spectroscopy provides valuable information on J-coupling constants for molecular structure analysis by resolving one-dimensional (1D) spectra. However, it is challenging to decipher the J-coupling connectivity in 2D J-resolved spectra because the J-coupling connectivity cannot be directly provided. In addition, 2D homonuclear correlation spectroscopy (COSY) can directly elucidate molecular structures by tracking the J-coupling connectivity between protons. However, this method is limited by the problem of spectral peak crowding and is only suitable for simple sample systems. To fully understand the intuitive coupling relationship and coupling constant information, we propose a three-dimensional (3D) COSY method called CTCOSY-JRES (Constant-Time COrrelation SpectroscopY and J-REsolved Spectroscopy) in this paper. By combining the J-resolved spectrum with the constant-time COSY technique, a doubly decoupled COSY spectrum can be provided while preserving the J-coupling constant along an additional dimension, ensuring high-resolution analysis of J-coupling connectivity and J-coupling information. Moreover, compression sensing and fold-over correction techniques are introduced to accelerate experimental acquisition. The CTCOSY-JRES method has been successfully validated in a variety of sample systems, including industrial, agricultural, and biopharmaceutical samples, revealing complex coupling interactions and providing deeper insights into the resolution of molecular structures.

Ultrafast 2D NMR for the analysis of complex mixtures

2D NMR is extensively used in many different fields, and its potential for the study of complex biochemical or chemical mixtures has been widely demonstrated. 2D NMR gives the ability to resolve peaks that overlap in 1D spectra, while providing both structural and quantitative information. However, complex mixtures are often analysed in situations where the data acquisition time is a crucial limitation, due to an ongoing chemical reaction or a moving sample from a hyphenated technique, or to the high-throughput requirement associated with large sample collections. Among the great diversity of available fast 2D methods, ultrafast (or single-scan) 2D NMR is probably the most general and versatile approach for complex mixture analysis. Indeed, ultrafast NMR has undergone an impressive number of methodological developments that have helped turn it into an efficient analytical tool, and numerous applications to the analysis of mixtures have been reported. This review first summarizes the main concepts, features and practical limitations of ultrafast 2D NMR, as well as the methodological developments that improved its analytical potential. Then, a detailed description of the main applications of ultrafast 2D NMR to mixture analysis is given. The two major application fields of ultrafast 2D NMR are first covered, i.e., reaction/process monitoring and metabolomics. Then, the potential of ultrafast 2D NMR for the analysis of hyperpolarized mixtures is described, as well as recent developments in oriented media. This review focuses on high-resolution liquid-state 2D experiments (including benchtop NMR) that include at least one spectroscopic dimension (i.e., 2D spectroscopy and DOSY) but does not cover in depth applications without spectral resolution and/or in inhomogeneous fields.

Rapid nuclear magnetic resonance data acquisition with improved resolution and sensitivity for high-throughput metabolomic analysis

Nuclear magnetic resonance (NMR)-based metabolomics has witnessed rapid advancements in recent years with the continuous development of new methods to enhance the sensitivity, resolution, and speed of data acquisition. Some of the approaches were earlier used for peptide and protein resonance assignments and have now been adapted to metabolomics. At the same time, new NMR methods involving novel data acquisition techniques, suited particularly for high-throughput analysis in metabolomics, have been developed. In this review, we focus on the different sampling strategies or data acquisition methods that have been developed in our laboratory and other groups to acquire NMR spectra rapidly with high sensitivity and resolution for metabolomics. In particular, we focus on the use of multiple receivers, phase modulation NMR spectroscopy, and fast-pulsing methods for identification and assignments of metabolites.

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.

The Design of FluxML: A Universal Modeling Language for 13C Metabolic Flux Analysis

¹³C metabolic flux analysis (MFA) is the method of choice when a detailed inference of intracellular metabolic fluxes in living organisms under metabolic quasi-steady state conditions is desired. Being continuously developed since two decades, the technology made major contributions to the quantitative characterization of organisms in all fields of biotechnology and health-related research. ¹³C MFA, however, stands out from other "-omics sciences," in that it requires not only experimental-analytical data, but also mathematical models and a computational toolset to infer the quantities of interest, i.e., the metabolic fluxes. At present, these models cannot be conveniently exchanged between different labs. Here, we present the implementation-independent model description language FluxML for specifying ¹³C MFA models. The core of FluxML captures the metabolic reaction network together with atom mappings, constraints on the model parameters, and the wealth of data configurations. In particular, we describe the governing design processes that shaped the FluxML language. We demonstrate the utility of FluxML to represent many contemporary experimental-analytical requirements in the field of ¹³C MFA. The major aim of FluxML is to offer a sound, open, and future-proof language to unambiguously express and conserve all the necessary information for model re-use, exchange, and comparison. Along with FluxML, several powerful computational tools are supplied for easy handling, but also to maintain a maximum of flexibility. Altogether, the FluxML collection is an "all-around carefree package" for ¹³C MFA modelers. We believe that FluxML improves scientific productivity as well as transparency and therewith contributes to the efficiency and reproducibility of computational modeling efforts in the field of ¹³C MFA.

Spatial encoding and spatial selection methods in high-resolution NMR spectroscopy

A family of high-resolution NMR methods share the common concept of acquiring in parallel different sub-experiments in different spatial regions of the NMR tube. These spatial encoding and spatial selection methods were for the most part introduced independently from each other and serve different purposes, but they share common ingredients, often derived from magnetic resonance imaging, and they all benefit from a greatly improved time-efficiency. This review article provides a description of several spatial encoding and spatial selection methods, including single-scan multidimensional experiments (ultrafast 2D NMR, DOSY, Z spectroscopy, inversion recovery and Laplace NMR), pure shift and selective refocusing experiments (including Zangger-Sterk decoupling, G-SERF and PSYCHE), a Z filter, and fast-pulsing slice-selective experiments. Some key elements for spatial parallelisation are introduced and when possible a common framework is used for the analysis of each method. Sensitivity considerations are discussed, and a selection of applications is analysed to illustrate which questions can be answered thanks to spatial encoding and spatial selection methods, and discuss the perspectives for future developments and applications.

Plant metabolism as studied by NMR spectroscopy

The study of plant metabolism impacts a broad range of domains such as plant cultural practices, plant breeding, human or animal nutrition, phytochemistry and green biotechnologies. Plant metabolites are extremely diverse in terms of structure or compound families as well as concentrations. This review attempts to illustrate how NMR spectroscopy, with its broad variety of experimental approaches, has contributed widely to the study of plant primary or specialized metabolism in very diverse ways. The review presents recent developments of one-dimensional and multi-dimensional NMR methods to study various aspects of plant metabolism. Through recent examples, it highlights how NMR has proved to be an invaluable tool for the global characterization of sample composition within metabolomic studies, and shows some examples of use for targeted phytochemistry, with a special focus on compound identification and quantitation. In such cases, NMR approaches are often used to provide snapshots of the plant sample composition. The review also covers dynamic aspects of metabolism, with a description of NMR techniques to measure metabolic fluxes - in most cases after stable isotope labelling. It is mainly intended for NMR specialists who would be interested to learn more about the potential of their favourite technique in plant sciences and about specific details of NMR approaches in this field. Therefore, as a practical guide, a paragraph on the specific precautions that should be taken for sample preparation is also included. In addition, since the quality of NMR metabolic studies is highly dependent on approaches to data processing and data sharing, a specific part is dedicated to these aspects. The review concludes with perspectives on the emerging methods that could change significantly the role of NMR in the field of plant metabolism by boosting its sensitivity. The review is illustrated throughout with examples of studies selected to represent diverse applications of liquid-state or HR-MAS NMR.

Combined maximum-quantum and DOSY 3D experiments provide enhanced resolution for small molecules in mixtures

We illustrate here as the combination of high-order maximum-quantum (MaxQ) and Diffusion-Ordered SpectroscopY (DOSY) NMR experiments in a 3D layout allows superior resolution for crowded NMR spectra. Non-uniform sampling (NUS) allows compressing the experimental time effectively to reasonable durations. Because diffusion effects were encoded within multiple-quantum coherences, increased sensitivity to magnetic field gradients is observed, requiring compensation for convection effects. The experiment was demonstrated on the spectra of a mix of small polyaromatic molecules. Specifically, in the case analyzed, the experiment provided an extreme simplification through the MaxQDOSY-MaxQ projection plane that presents one peak per molecule. Copyright © 2016 John Wiley & Sons, Ltd.

Ultrafast acquisition of 1H-1H dipolar correlation experiments in spinning elastomers

We show that two widely used 2D solid-state NMR (ssNMR) pulse sequences can be implemented in an ultrafast (UF) manner, and yield 2D spectra of elastomers in a single scan, under magic-angle spinning. UF 2D ssNMR provides an acceleration of one to several orders of magnitude for classic experiments.

Fast hybrid multi-dimensional NMR methods based on ultrafast 2D NMR

Conventional multi-dimensional (nD) NMR experiments are characterized by inherent long acquisition durations, while ultrafast (UF) NMR makes it possible to reduce to a few hundreds of milliseconds the overall acquisition duration of a complete nD NMR dataset. Although extremely promising for a number of specific applications, the UF strategy suffers from significant limitations compared with its conventional counterpart. The main limitations concern the sensitivity, the resolution, and the accessible spectral width. However, when the targeted applications are compatible with an acquisition duration between a few seconds and a few minutes, hybrid UF techniques can be used to improve the performance of UF nD NMR while remaining faster than conventional acquisitions. Much better results in terms of signal-to-noise ratio can be achieved with the multi-scan single-shot approach or with interleaved acquisitions. Even more, for the same experimental duration, and in the case of homonuclear 2D NMR, the multi-scan single-shot approach has a much higher precision than conventional 2D NMR. Interleaved 2D NMR overcomes the drawbacks of single-scan UF NMR in terms of spectral width and provides spectra for which the quality is not significantly different from that obtained with conventional 2D NMR. Finally, high spectral qualities have been demonstrated from hybrid conventional/UF 3D approaches capable of recording a whole 3D spectrum in the time needed to record a conventional 2D spectrum. This mini-review aims at describing the principles, the recent advances and the latest applications of these hybrid techniques. Copyright © 2015 John Wiley & Sons, Ltd.

Multidimensional NMR spectroscopy in a single scan

Multidimensional NMR has become one of the most widespread spectroscopic tools available to study diverse structural and functional aspects of organic and biomolecules. A main feature of multidimensional NMR is the relatively long acquisition times that these experiments demand. For decades, scientists have been working on a variety of alternatives that would enable NMR to overcome this limitation, and deliver its data in shorter acquisition times. Counting among these methodologies is the so-called ultrafast (UF) NMR approach, which in principle allows one to collect arbitrary multidimensional correlations in a single sub-second transient. By contrast to conventional acquisitions, a main feature of UF NMR is a spatiotemporal manipulation of the spins that imprints the chemical shift and/or J-coupling evolutions being sought, into a spatial pattern. Subsequent gradient-based manipulations enable the reading out of this information and its multidimensional correlation into patterns that are identical to those afforded by conventional techniques. The current review focuses on the fundamental principles of this spatiotemporal UF NMR manipulation, and on a few of the methodological extensions that this form of spectroscopy has undergone during the years.

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.

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.

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.

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.

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.