Highly Repeatable Dissolution Dynamic Nuclear Polarization for Heteronuclear NMR Metabolomics

Hyperpolarization-Enhanced NMR Spectroscopy of Unaltered Biofluids Using Photo-CIDNP

The direct and unambiguous detection and identification of individual metabolite molecules present in complex biological mixtures constitute a major challenge in (bio)analytical research. In this context, nuclear magnetic resonance (NMR) spectroscopy has proven to be particularly powerful owing to its ability to provide both qualitative and quantitative atomic-level information on multiple analytes simultaneously in a noninvasive manner. Nevertheless, NMR suffers from a low inherent sensitivity and, moreover, lacks selectivity regarding the number of individual analytes to be studied in a mixture of a myriad of structurally and chemically very different molecules, e.g., metabolites in a biofluid. Here, we describe a method that circumvents these shortcomings via performing selective, photochemically induced dynamic nuclear polarization (photo-CIDNP) enhanced NMR spectroscopy on unmodified complex biological mixtures, i.e., human urine and serum, which yields a single, background-free one-dimensional NMR spectrum. In doing this, we demonstrate that photo-CIDNP experiments on unmodified complex mixtures of biological origin are feasible, can be performed straightforwardly in the native aqueous medium at physiological metabolite concentrations, and act as a spectral filter, facilitating the analysis of NMR spectra of complex biofluids. Due to its noninvasive nature, the method is fully compatible with state-of-the-art metabolomic protocols providing direct spectroscopic information on a small, carefully selected subset of clinically relevant metabolites. We anticipate that this approach, which, in addition, can be combined with existing high-throughput/high-sensitivity NMR methodology, holds great promise for further in-depth studies and development for use in metabolomics and many other areas of analytical research.

Present and future of pure shift NMR in metabolomics

NMR is one of the most powerful techniques for the analysis of biological samples in the field of metabolomics. However, the high complexity of fluids, tissues, or other biological materials taken from living organisms is still a challenge for state-of-the-art pulse sequences, thereby limiting the detection, the identification, and the quantification of metabolites. In this context, the resolution enhancement provided by broadband homonuclear decoupling methods, which allows for simplifying 1 H multiplet patterns into singlets, has placed this so-called pure shift technique as a promising approach to perform metabolic profiling with unparalleled level of detail. In recent years, the many advances achieved in the design of pure shift experiments has paved the way to the analysis of a wide range of biological samples with ultra-high resolution. This review leads the reader from the early days of the main pure shift methods that have been successfully developed over the last decades to address complex samples, to the most recent and promising applications of pure shift NMR to the field of NMR-based metabolomics.

Optimization of heteronuclear ultrafast 2D NMR for the study of complex mixtures hyperpolarized by dynamic nuclear polarization

Hyperpolarized 13C NMR at natural abundance, based on dissolution dynamic nuclear polarization (d-DNP), provides rich, sensitive and repeatable 13C NMR fingerprints of complex mixtures. However, the sensitivity enhancement is associated with challenges such as peak overlap and the difficulty to assign hyperpolarized 13C signals. Ultrafast (UF) 2D NMR spectroscopy makes it possible to record heteronuclear 2D maps of d-DNP hyperpolarized samples. Heteronuclear UF 2D NMR can provide correlation peaks that link quaternary carbons and protons through long-range scalar couplings. Here, we report the analytical assessment of an optimized UF long-range HETCOR pulse sequence, applied to the detection of metabolic mixtures at natural abundance and hyperpolarized by d-DNP, based on repeatability and sensitivity considerations. We show that metabolite-dependent limits of quantification in the range of 1-50 mM (in the sample before dissolution) can be achieved, with a repeatability close to 10% and a very good linearity. We provide a detailed comparison of such analytical performance in two different dissolution solvents, D2O and MeOD. The reported pulse sequence appears as an useful analytical tool to facilitate the assignment and integration of metabolite signals in hyperpolarized complex mixtures.

Hyperpolarized 1H and 13C NMR Spectroscopy in a Single Experiment for Metabolomics

The application of NMR spectroscopy to complex mixture analysis and, in particular, to metabolomics is limited by the low sensitivity of NMR. We recently showed that dissolution dynamic nuclear polarization (d-DNP) could enhance the sensitivity of 13C NMR for complex metabolite mixtures, leading to the detection of highly sensitive 13C NMR fingerprints of complex samples such as plant extracts or urine. While such experiments provide heteronuclear spectra, which are complementary to conventional NMR, hyperpolarized 1H NMR spectra would also be highly useful, with improved limits of detection and compatibility with the existing metabolomics workflow and databases. In this technical note, we introduce an approach capable of recording both 1H and 13C hyperpolarized spectra of metabolite mixtures in a single experiment and on the same hyperpolarized sample. We investigate the analytical performance of this method in terms of sensitivity and repeatability, and then we show that it can be efficiently applied to a plant extract. Significant sensitivity enhancements in 1H NMR are reported with a repeatability suitable for metabolomics studies without compromising on the performance of hyperpolarized 13C NMR. This approach provides a way to perform both 1H and 13C hyperpolarized NMR metabolomics with unprecedented sensitivity and throughput.

Hyperpolarized NMR metabolomics

Hyperpolarized NMR is a promising approach to address the sensitivity limits of conventional NMR metabolomics approaches, which currently fails to detect minute metabolite concentrations in biological samples. This review describes how tremendous signal enhancement offered by dissolution-dynamic nuclear polarization and parahydrogen-based techniques can be fully exploited for molecular omics sciences. Recent developments, including the combination of hyperpolarization techniques with fast multi-dimensional NMR implementation and quantitative workflows are described, and a comprehensive comparison of existing hyperpolarization techniques is proposed. High-throughput, sensitivity, resolution and other relevant challenges that should be tackled for a general application of hyperpolarized NMR in metabolomics are discussed.

Spin Hyperpolarization in Modern Magnetic Resonance

Magnetic resonance techniques are successfully utilized in a broad range of scientific disciplines and in various practical applications, with medical magnetic resonance imaging being the most widely known example. Currently, both fundamental and applied magnetic resonance are enjoying a major boost owing to the rapidly developing field of spin hyperpolarization. Hyperpolarization techniques are able to enhance signal intensities in magnetic resonance by several orders of magnitude, and thus to largely overcome its major disadvantage of relatively low sensitivity. This provides new impetus for existing applications of magnetic resonance and opens the gates to exciting new possibilities. In this review, we provide a unified picture of the many methods and techniques that fall under the umbrella term "hyperpolarization" but are currently seldom perceived as integral parts of the same field. Specifically, before delving into the individual techniques, we provide a detailed analysis of the underlying principles of spin hyperpolarization. We attempt to uncover and classify the origins of hyperpolarization, to establish its sources and the specific mechanisms that enable the flow of polarization from a source to the target spins. We then give a more detailed analysis of individual hyperpolarization techniques: the mechanisms by which they work, fundamental and technical requirements, characteristic applications, unresolved issues, and possible future directions. We are seeing a continuous growth of activity in the field of spin hyperpolarization, and we expect the field to flourish as new and improved hyperpolarization techniques are implemented. Some key areas for development are in prolonging polarization lifetimes, making hyperpolarization techniques more generally applicable to chemical/biological systems, reducing the technical and equipment requirements, and creating more efficient excitation and detection schemes. We hope this review will facilitate the sharing of knowledge between subfields within the broad topic of hyperpolarization, to help overcome existing challenges in magnetic resonance and enable novel applications.

NMR methods for the analysis of mixtures

NMR spectroscopy is a powerful approach for the analysis of mixtures. Its usefulness arises in large part from the vast landscape of methods, and corresponding pulse sequences, that have been and are being designed to tackle the specific properties of mixtures of small molecules. This feature article describes a selection of methods that aim to address the complexity, the low concentrations, and the changing nature that mixtures can display. These notably include pure-shift and diffusion NMR methods, hyperpolarisation methods, and fast 2D NMR methods such as ultrafast 2D NMR and non-uniform sampling. Examples or applications are also described, in fields such as reaction monitoring and metabolomics, to illustrate the relevance and limitations of different methods.

Fine optimization of a dissolution dynamic nuclear polarization experimental setting for 13C NMR of metabolic samples

NMR-based analysis of metabolite mixtures provides crucial information on biological systems but mostly relies on 1D 1 H experiments for maximizing sensitivity. However, strong peak overlap of 1 H spectra often is a limitation for the analysis of inherently complex biological mixtures. Dissolution dynamic nuclear polarization (d-DNP) improves NMR sensitivity by several orders of magnitude, which enables 13 C NMR-based analysis of metabolites at natural abundance. We have recently demonstrated the successful introduction of d-DNP into a full untargeted metabolomics workflow applied to the study of plant metabolism. Here we describe the systematic optimization of d-DNP experimental settings for experiments at natural 13 C abundance and show how the resolution, sensitivity, and ultimately the number of detectable signals improve as a result. We have systematically optimized the parameters involved (in a semi-automated prototype d-DNP system, from sample preparation to signal detection, aiming at providing an optimization guide for potential users of such a system, who may not be experts in instrumental development). The optimization procedure makes it possible to detect previously inaccessible protonated 13 C signals of metabolites at natural abundance with at least 4 times improved line shape and a high repeatability compared to a previously reported d-DNP-enhanced untargeted metabolomic study. This extends the application scope of hyperpolarized 13 C NMR at natural abundance and paves the way to a more general use of DNP-hyperpolarized NMR in metabolomics studies.

Interfacing Liquid State Hyperpolarization Methods with NMR Instrumentation

Advances in liquid state hyperpolarization methods have enabled new applications of high-resolution NMR spectroscopy. Utilizing strong signal enhancements from hyperpolarization allows performing NMR spectroscopy at low concentration, or with high time resolution. Making use of the high, but rapidly decaying hyperpolarization in the liquid state requires new techniques to interface hyperpolarization equipment with liquid state NMR spectrometers. This article highlights rapid injection, high resolution NMR spectroscopy with hyperpolarization produced by the techniques of dissolution dynamic nuclear polarization (D-DNP) and para-hydrogen induced polarization (PHIP). These are popular, albeit not the only methods to produce high polarization levels for liquid samples. Gas and liquid driven sample injection techniques are compatible with both of these hyperpolarization methods. The rapid sample injection techniques are combined with adapted NMR experiments working in a single, or small number of scans. They expand the application of liquid state hyperpolarization to spins with comparably short relaxation times, provide enhanced control over sample conditions, and allow for mixing experiments to study reactions in real time.

Classification and biomarker identification of prostate tissue from TRAMP mice with hyperpolarized 13C-SIRA

Hyperpolarized ¹³C isotope resolved spectroscopy boosts NMR signal intensity, which improves signal detection and allows metabolic fluxes to be analyzed. Such hyperpolarized flux data may offer new approaches to tissue classification and biomarker identification that could be translated in vivo. Here we used hyperpolarized stable isotope resolved analysis (SIRA) to measure metabolite specific ¹³C isotopic enrichments in the central carbon metabolism of mouse prostate. Prostate and tumor tissue samples were acquired from transgenic adenocarcinomas of the mouse prostate (TRAMP) mice. Before euthanasia, mice were injected with [U-¹³C]glucose intraperitoneally (i.p.). Polar metabolite extracts were prepared, and hyperpolarized 1D-¹³C NMR spectra were obtained from normal prostate (n = 19) and cancer tissue (n = 19) samples. Binary classification and feature analysis was performed to make a separation model and to investigate differences between samples originating from normal and cancerous prostate tissue, respectively. Hyperpolarized experiments were carried out according to a standardized protocol, which showed a high repeatability (CV = 15%) and an average linewidth in the 1D-¹³C NMR spectra of 2 ± 0.5 Hz. The resolution of the hyperpolarized 1D-¹³C spectra was high with little signal overlap in the carbonyl region and metabolite identification was easily accomplished. A discrimination with 95% success rate could be made between samples originating from TRAMP mice prostate and tumor tissue based on isotopomers from uniquely identified metabolites. Hyperpolarized ¹³C-SIRA allowed detailed metabolic information to be obtained from tissue specimens. The positional information of ¹³C isotopic enrichments lead to easily interpreted features responsible for high predictive classification of tissue types. This analytical approach has matured, and the robust experimental protocols currently available allow systematic tracking of metabolite flux ex vivo.

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.

Practical dissolution dynamic nuclear polarization

This review article intends to provide insightful advice for dissolution-dynamic nuclear polarization in the form of a practical handbook. The goal is to aid research groups to effectively perform such experiments in their own laboratories. Previous review articles on this subject have covered a large number of useful topics including instrumentation, experimentation, theory, etc. The topics to be addressed here will include tips for sample preparation and for checking sample health; a checklist to correctly diagnose system faults and perform general maintenance; the necessary mechanical requirements regarding sample dissolution; and aids for accurate, fast and reliable polarization quantification. Herein, the challenges and limitations of each stage of a typical dissolution-dynamic nuclear polarization experiment are presented, with the focus being on how to quickly and simply overcome some of the limitations often encountered in the laboratory.

Metabolomics-Guided Elucidation of Plant Abiotic Stress Responses in the 4IR Era: An Overview

Plants are constantly challenged by changing environmental conditions that include abiotic stresses. These are limiting their development and productivity and are subsequently threatening our food security, especially when considering the pressure of the increasing global population. Thus, there is an urgent need for the next generation of crops with high productivity and resilience to climate change. The dawn of a new era characterized by the emergence of fourth industrial revolution (4IR) technologies has redefined the ideological boundaries of research and applications in plant sciences. Recent technological advances and machine learning (ML)-based computational tools and omics data analysis approaches are allowing scientists to derive comprehensive metabolic descriptions and models for the target plant species under specific conditions. Such accurate metabolic descriptions are imperatively essential for devising a roadmap for the next generation of crops that are resilient to environmental deterioration. By synthesizing the recent literature and collating data on metabolomics studies on plant responses to abiotic stresses, in the context of the 4IR era, we point out the opportunities and challenges offered by omics science, analytical intelligence, computational tools and big data analytics. Specifically, we highlight technological advancements in (plant) metabolomics workflows and the use of machine learning and computational tools to decipher the dynamics in the chemical space that define plant responses to abiotic stress conditions.

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.

Metabolomics: An emerging potential approach to decipher critical illnesses

Critical illnesses contribute to the maximum morbidity and mortality of hospitalized patients. Acute respiratory distress syndrome (ARDS) and sepsis/septic shock are the two most common acute illnesses associated with intensive care unit (ICU) admission. Once triggered, both have an identical underlying mechanism, portrayed by inflammation and endothelial dysfunction. The diagnosis of ARDS is based on clinical findings, laboratory tests, and radiological imaging. Blood cultures remain the gold standard for the diagnosis of sepsis, with the limitation of time delay and low positive yield. A combination of biomarkers has been proposed to diagnose and prognosticate these acute disorders with strengths and limitations, but still, the gold standard has been elusive to clinicians. In this review article, we illustrate the potential of metabolomics to unravel biomarkers that can be clinically utilized as a rapid prognostic and diagnostic tool associated with specific patient populations (ARDS and sepsis/septic shock) based on the available scientific data.

Hyperpolarized NMR Metabolomics at Natural 13C Abundance

Metabolomics plays a pivotal role in systems biology, and NMR is a central tool with high precision and exceptional resolution of chemical information. Most NMR metabolomic studies are based on 1H 1D spectroscopy, severely limited by peak overlap. 13C NMR benefits from a larger signal dispersion but is barely used in metabolomics due to ca. 6000-fold lower sensitivity. We introduce a new approach, based on hyperpolarized 13C NMR at natural abundance, that circumvents this limitation. A new untargeted NMR-based metabolomic workflow based on dissolution dynamic nuclear polarization (d-DNP) for the first time enabled hyperpolarized natural abundance 13C metabolomics. Statistical analysis of resulting hyperpolarized 13C data distinguishes two groups of plant (tomato) extracts and highlights biomarkers, in full agreement with previous results on the same biological model. We also optimize parameters of the semiautomated d-DNP system suitable for high-throughput studies.

Stable isotope resolved metabolomics classification of prostate cancer cells using hyperpolarized NMR data

Metabolic fingerprinting is a strong tool for characterization of biological phenotypes. Classification with machine learning is a critical component in the discrimination of molecular determinants. Cellular activity can be traced using stable isotope labelling of metabolites from which information on cellular pathways may be obtained. Nuclear magnetic resonance (NMR) spectroscopy is, due to its ability to trace labelling in specific atom positions, a method of choice for such metabolic activity measurements. In this study, we used hyperpolarization in the form of dissolution Dynamic Nuclear Polarization (dDNP) NMR to measure signal enhanced isotope labelled metabolites reporting on pathway activity from four different prostate cancer cell lines. The spectra have a high signal-to-noise, with less than 30 signals reporting on 10 metabolic reactions. This allows easy extraction and straightforward interpretation of spectral data. Four metabolite signals selected using a Random Forest algorithm allowed a classification with Support Vector Machines between aggressive and indolent cancer cells with 96.9% accuracy, -corresponding to 31 out of 32 samples. This demonstrates that the information contained in the few features measured with dDNP NMR, is sufficient and robust for performing binary classification based on the metabolic activity of cultured prostate cancer cells.

Dipolar order mediated 1H → 13C cross-polarization for dissolution-dynamic nuclear polarization

Magnetic resonance imaging and spectroscopy often suffer from a low intrinsic sensitivity, which can in some cases be circumvented by the use of hyperpolarization techniques. Dissolution-dynamic nuclear polarization offers a way of hyperpolarizing 13 C spins in small molecules, enhancing their sensitivity by up to 4 orders of magnitude. This is usually performed by direct 13 C polarization, which is straightforward but often takes more than an hour. Alternatively, indirect 1 H polarization followed by 1 H → 13 C polarization transfer can be implemented, which is more efficient and faster but is technically very challenging and hardly implemented in practice. Here we propose to remove the main roadblocks of the 1 H → 13 C polarization transfer process by using alternative schemes with the following: (i) less rf (radiofrequency) power; (ii) less overall rf energy; (iii) simple rf-pulse shapes; and (iv) no synchronized 1 H and 13 C rf irradiation. An experimental demonstration of such a simple 1 H → 13 C polarization transfer technique is presented for the case of [1-13 C ]sodium acetate, and is compared with the most sophisticated cross-polarization schemes. A polarization transfer efficiency of ∼ 0.43 with respect to cross-polarization was realized, which resulted in a 13 C polarization of ∼ 8.7  % after ∼ 10  min of microwave irradiation and a single polarization transfer step.

Analysis of NMR Metabolomics Data

In this chapter, we summarize data preprocessing and data analysis strategies used for analysis of NMR data for metabolomics studies. Metabolomics consists of the analysis of the low molecular weight compounds in cells, tissues, or biological fluids, and has been used to reveal biomarkers for early disease detection and diagnosis, to monitor interventions, and to provide information on pathway perturbations to inform mechanisms and identifying targets. Metabolic profiling (also termed metabotyping) involves the analysis of hundreds to thousands of molecules using mainly state-of-the-art mass spectrometry (MS) and nuclear magnetic resonance (NMR) spectroscopy technologies. While NMR is less sensitive than mass spectrometry, NMR does provide a wealth of complex and information rich metabolite data. NMR data together with the use of conventional statistics, modeling methods, and bioinformatics tools reveals biomarker and mechanistic information. A typical NMR spectrum, with up to 64k data points, of a complex biological fluid or an extract of cells and tissues consists of thousands of sharp signals that are mainly derived from small molecules. In addition, a number of advanced NMR spectroscopic methods are available for extracting information on high molecular weight compounds such as lipids or lipoproteins. There are numerous data preprocessing, data reduction, and analysis methods developed and evolving in the field of NMR metabolomics. Our goal is to provide an extensive summary of NMR data preprocessing and analysis strategies by providing examples and open source and commercially available analysis software and bioinformatics tools.

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.

NMR metabolomics: A look ahead

NMR has been used to perform metabolic studies, metabolic profiling and metabolomics in biofluids and tissues for more than 40 years. This close connection between metabolic measurements and NMR has flourished because of NMR's many unique strengths for characterizing the chemical composition of complex mixtures. However, a number of other technologies, including mass spectrometry, have appeared in the past few years that are encroaching on NMR's dominance in metabolomics and metabolic studies. In this brief review, some of the current strengths and existing limitations of NMR-based metabolomics are highlighted. Additionally, a number of recent advances in NMR hardware, methodology and software are also described and these advancements are used to speculate about where NMR-based metabolomics is going, what needs to be done to make it more popular and how it will evolve in the next 5-10 years.

Application and methodology of dissolution dynamic nuclear polarization in physical, chemical and biological contexts

Dissolution dynamic nuclear polarization (d-DNP) is a versatile method to enhance nuclear magnetic resonance (NMR) spectroscopy. It boosts signal intensities by four to five orders of magnitude thereby providing the potential to improve and enable a plethora of applications ranging from the real-time monitoring of chemical or biological processes to metabolomics and in-cell investigations. This perspectives article highlights possible avenues for developments and applications of d-DNP in biochemical and physicochemical studies. It outlines how chemists, biologists and physicists with various fields of interest can transform and employ d-DNP as a powerful characterization method for their research.

NMR Spectroscopy for Metabolomics Research

Over the past two decades, nuclear magnetic resonance (NMR) has emerged as one of the three principal analytical techniques used in metabolomics (the other two being gas chromatography coupled to mass spectrometry (GC-MS) and liquid chromatography coupled with single-stage mass spectrometry (LC-MS)). The relative ease of sample preparation, the ability to quantify metabolite levels, the high level of experimental reproducibility, and the inherently nondestructive nature of NMR spectroscopy have made it the preferred platform for long-term or large-scale clinical metabolomic studies. These advantages, however, are often outweighed by the fact that most other analytical techniques, including both LC-MS and GC-MS, are inherently more sensitive than NMR, with lower limits of detection typically being 10 to 100 times better. This review is intended to introduce readers to the field of NMR-based metabolomics and to highlight both the advantages and disadvantages of NMR spectroscopy for metabolomic studies. It will also explore some of the unique strengths of NMR-based metabolomics, particularly with regard to isotope selection/detection, mixture deconvolution via 2D spectroscopy, automation, and the ability to noninvasively analyze native tissue specimens. Finally, this review will highlight a number of emerging NMR techniques and technologies that are being used to strengthen its utility and overcome its inherent limitations in metabolomic applications.

Natural Abundance, Single-Scan 13C-13C-Based Structural Elucidations by Dissolution DNP NMR

While ¹³C-based Incredible Natural Abundance DoublE QUAntum Transfer Experiment (INADEQUATE) experiments offer an attractive alternative for establishing molecular structures, they suffer from low sensitivities arising from the scarcity of spin pairs present at natural abundance. Herein we demonstrate that dissolution dynamic nuclear polarization (dDNP) provides sufficient sensitivity to acquire 1D ¹³C INADEQUATE spectra in a single scan and at natural abundance. Moreover, if steps are adopted to endow sub-Hertz precision to these measurements, they allow one to measure carbon-carbon J couplings over both one and multiple bonds for each chemical site. As these J_CC-couplings are usually sufficiently distinct to enable univocal pairing of the nuclei involved, essentially the same information as in 2D INADEQUATE can be obtained. The feasibility of the method is demonstrated for a range of compounds, including natural products such as α-pinene, menthol and limonene. Features and extensions of this approach are briefly discussed.

Recent Advances in Targeted and Untargeted Metabolomics by NMR and MS/NMR Methods

Metabolomics has made significant progress in multiple fronts in the last 18 months. This minireview aimed to give an overview of these advancements in the light of their contribution to targeted and untargeted metabolomics. New computational approaches have emerged to overcome the manual absolute quantitation step of metabolites in one-dimensional (1D) ¹H nuclear magnetic resonance (NMR) spectra. This provides more consistency between inter-laboratory comparisons. Integration of two-dimensional (2D) NMR metabolomics databases under a unified web server allowed for very accurate identification of the metabolites that have been catalogued in these databases. For the remaining uncatalogued and unknown metabolites, new cheminformatics approaches have been developed by combining NMR and mass spectrometry (MS). These hybrid MS/NMR approaches accelerated the identification of unknowns in untargeted studies, and now they are allowing for profiling ever larger number of metabolites in application studies.

Dynamic Nuclear Polarization Opens New Perspectives for NMR Spectroscopy in Analytical Chemistry

Dynamic nuclear polarization (DNP) can boost sensitivity in nuclear magnetic resonance (NMR) experiments by several orders of magnitude. This Feature illustrates how the coupling of DNP with both liquid- and solid-state NMR spectroscopy has the potential to considerably extend the range of applications of NMR in analytical chemistry.

Chemical Exchange Saturation Transfer in Chemical Reactions: A Mechanistic Tool for NMR Detection and Characterization of Transient Intermediates

The low sensitivity of NMR and transient key intermediates below detection limit are the central problems studying reaction mechanisms by NMR. Sensitivity can be enhanced by hyperpolarization techniques such as dynamic nuclear polarization or the incorporation/interaction of special hyperpolarized molecules. However, all of these techniques require special equipment, are restricted to selective reactions, or undesirably influence the reaction pathways. Here, we apply the chemical exchange saturation transfer (CEST) technique for the first time to NMR detect and characterize previously unobserved transient reaction intermediates in organocatalysis. The higher sensitivity of CEST and chemical equilibria present in the reaction pathway are exploited to access population and kinetics information on low populated intermediates. The potential of the method is demonstrated on the proline-catalyzed enamine formation for unprecedented in situ detection of a DPU stabilized zwitterionic iminium species, the elusive key intermediate between enamine and oxazolidinones. The quantitative analysis of CEST data at 250 K revealed the population ratio of [Z-iminium]/[exo-oxazolidinone] 0.02, relative free energy +8.1 kJ/mol (calculated +7.3 kJ/mol), and free energy barrier of +45.9 kJ/mol (ΔG^⧧_calc.(268 K) = +42.2 kJ/mol) for Z-iminium → exo-oxazolidinone. The findings underpin the iminium ion participation in enamine formation pathway corroborating our earlier theoretical prediction and help in better understanding. The reliability of CEST is validated using 1D EXSY-build-up techniques at low temperature (213 K). The CEST method thus serves as a new tool for mechanistic investigations in organocatalysis to access key information, such as chemical shifts, populations, and reaction kinetics of intermediates below the standard NMR detection limit.

Stable Isotope-Resolved Analysis with Quantitative Dissolution Dynamic Nuclear Polarization

Metabolite profiles and their isotopomer distributions can be studied noninvasively in complex mixtures with NMR. The advent of dissolution Dynamic Nuclear Polarization (dDNP) and isotope enrichment add sensitivity and resolution to such metabolic studies. Metabolic pathways and networks can be mapped and quantified if protocols that control and exploit the ex situ signal enhancement are created. We present a sample preparation method, including cell incubation, extraction and signal enhancement, to obtain reproducible and quantitative dDNP (qdDNP) NMR-based stable isotope-resolved analysis. We further illustrate how qdDNP was applied to gain metabolic insights into the phenotype of aggressive cancer cells.

1H NMR Metabolic Profiling of Earthworm (Eisenia fetida) Coelomic Fluid, Coelomocytes, and Tissue: Identification of a New Metabolite-Malylglutamate

Earthworm metabolism is recognized as a useful tool for monitoring environmental insults and measuring ecotoxicity, yet extensive earthworm metabolic profiling using ¹H nuclear magnetic resonance (NMR) spectroscopy has been limited in scope. This study aims to expand the embedded metabolic material in earthworm coelomic fluid, coelomocytes, and tissue to aid systems toxicology research. Fifty-nine metabolites within Eisenia fetida were identified, with 47 detected in coelomic fluid, 41 in coelomocytes, and 54 in whole-worm samples and tissue extracts. The newly detected but known metabolites 2-aminobutyrate, nicotinurate, Nδ,Nδ,Nδ-trimethylornithine, and trigonelline are reported along with a novel compound, malylglutamate, elucidated using 2D NMR and high-resolution MS/MS. We postulate that malylglutamate acts as a glutamate/malate store, chelator, and anionic osmolyte and helps to provide electrolyte balance.

New frontiers in metabolomics: from measurement to insight

Metabolomics is the newest addition to the "omics" disciplines and has shown rapid growth in its application to human health research because of fundamental advancements in measurement and analysis techniques. Metabolomics has unique and proven advantages in systems biology and biomarker discovery. The next generation of analysis techniques promises even richer and more complete analysis capabilities that will enable earlier clinical diagnosis, drug refinement, and personalized medicine. A review of current advancements in methodologies and statistical analysis that are enhancing and improving the performance of metabolomics is presented along with highlights of some recent successful applications.

Chiral Recognition by Dissolution DNP NMR Spectroscopy of 13C-Labeled dl-Methionine

A method based on d-DNP NMR spectroscopy to study chiral recognition is described for the first time. The enantiodifferentiation of a racemic metabolite in a millimolar aqueous solution using a chiral solvating agent was performed. Hyperpolarized ¹³C-labeled dl-methionine enantiomers were differently observed with a single-scan ¹³C NMR experiment, while the chiral auxiliary at thermal equilibrium remained unobserved. The method developed entails a step forward in the chiral recognition of small molecules by NMR spectroscopy, opening new possibilities in situations where the sensitivity is limited, for example, when a low concentration of analyte is available or when the measurement of an insensitive nucleus, like ¹³C, is required. The advantages and current limitations of the method, as well as future perspectives, are discussed.

NMRProcFlow: a graphical and interactive tool dedicated to 1D spectra processing for NMR-based metabolomics

INTRODUCTION

Concerning NMR-based metabolomics, 1D spectra processing often requires an expert eye for disentangling the intertwined peaks.

OBJECTIVES

The objective of NMRProcFlow is to assist the expert in this task in the best way without requirement of programming skills.

METHODS

NMRProcFlow was developed to be a graphical and interactive 1D NMR (1H & 13C) spectra processing tool.

RESULTS

NMRProcFlow (http://nmrprocflow.org), dedicated to metabolic fingerprinting and targeted metabolomics, covers all spectra processing steps including baseline correction, chemical shift calibration and alignment.

CONCLUSION

Biologists and NMR spectroscopists can easily interact and develop synergies by visualizing the NMR spectra along with their corresponding experimental-factor levels, thus setting a bridge between experimental design and subsequent statistical analyses.

Quantitative Metabolite Profiling of an Amino Group Containing Pharmaceutical in Human Plasma via Precolumn Derivatization and High-Performance Liquid Chromatography-Inductively Coupled Plasma Mass Spectrometry

Quantitative determination of the candidate drug molecule and its metabolites in biofluids and tissues is an inevitable step in the development of new pharmaceuticals. Because of the time-consuming and expensive nature of the current standard technique for quantitative metabolite profiling, i.e., radiolabeling followed by high-performance liquid chromatography (HPLC) with radiodetection, the development of alternative methodologies is of great interest. In this work, a simple, fast, sensitive, and accurate method for the quantitative metabolite profiling of an amino group containing drug (levothyroxine) and its metabolites in human plasma, based on precolumn derivatization followed by HPLC-inductively coupled plasma mass spectrometry (ICPMS), was developed and validated. To introduce a suitable "heteroelement" (defined here as an element that is detectable with ICPMS), an inexpensive and commercially available reagent, tetrabromophthalic anhydride (TBPA) was used for the derivatization of free NH₂-groups. The presence of a known number of I atoms in both the drug molecule and its metabolites enabled a cross-validation of the newly developed derivatization procedure and quantification based on monitoring of the introduced Br. The formation of the derivatives was quantitative, providing a 4:1 stoichiometric Br/NH₂ ratio. The derivatives were separated via reversed-phase HPLC with gradient elution. Bromine was determined via ICPMS at a mass-to-charge ratio of 79 using H₂ as a reaction gas to ensure interference-free detection, and iodine was determined at a mass-to-charge ratio of 127 for cross-validation purposes. The method developed shows a fit-for-purpose accuracy (recovery between 85% and 115%) and precision (repeatability <15% RSD). The limit of quantification (LoQ) for Br was approximately 100 μg/L.

Perspectives on hyperpolarised solution-state magnetic resonance in chemistry

This perspective article reviews some of the recent developments in the field of hyperpolarisation, with a focus on solution-state NMR spectroscopy of small molecules. Two techniques are considered in more detail, dissolution dynamic nuclear polarisation (D-DNP) and signal amplification by reversible exchange (SABRE). Some of the opportunities and challenges for applications of hyperpolarised solution-state magnetic resonance in chemistry are discussed. Copyright © 2016 John Wiley & Sons, Ltd.

Challenges and perspectives in quantitative NMR

This perspective article summarizes, from the author's point of view at the beginning of 2016, the major challenges and perspectives in the field of quantitative NMR. The key concepts in quantitative NMR are first summarized; then, the most recent evolutions in terms of resolution and sensitivity are discussed, as well as some potential future research directions in this field. A particular focus is made on methodologies capable of boosting the resolution and sensitivity of quantitative NMR, which could open application perspectives in fields where the sample complexity and the analyte concentrations are particularly challenging. These include multi-dimensional quantitative NMR and hyperpolarization techniques such as para-hydrogen-induced polarization or dynamic nuclear polarization. Because quantitative NMR cannot be dissociated from the key concepts of analytical chemistry, i.e. trueness and precision, the methodological developments are systematically described together with their level of analytical performance. Copyright © 2016 John Wiley & Sons, Ltd.

Multidimensional NMR approaches towards highly resolved, sensitive and high-throughput quantitative metabolomics

Multi-dimensional NMR is an appealing approach for dealing with the challenging complexity of biological samples in metabolomics. This article describes how spectroscopists have recently challenged their imagination in order to make 2D NMR a powerful tool for quantitative metabolomics, based on innovative pulse sequences combined with meticulous analytical chemistry approaches. Clever time-saving strategies have also been explored to make 2D NMR a high-throughput tool for metabolomics, relying on alternative data acquisition schemes such as ultrafast NMR. Currently, much work is aimed at drastically boosting the NMR sensitivity thanks to hyperpolarisation techniques, which have been used in combination with fast acquisition methods and could greatly expand the application potential of NMR metabolomics.