Quantitative NMR for bioanalysis and metabolomics

Over the last several decades, significant technical and experimental advances have made quantitative nuclear magnetic resonance (qNMR) a valuable analytical tool for quantitative measurements on a wide variety of samples. In particular, qNMR has emerged as an important method for metabolomics studies where it is used for interrogation of large sets of biological samples and the resulting spectra are treated with multivariate statistical analysis methods. In this review, recent developments in instrumentation and pulse sequences will be discussed as well as the practical considerations necessary for acquisition of quantitative NMR experiments with an emphasis on their use for bioanalysis. Recent examples of the application of qNMR for metabolomics/metabonomics studies, the characterization of biologicals such as heparin, antibodies, and vaccines, and the analysis of botanical natural products will be presented and the future directions of qNMR discussed.     

Targeted projection NMR spectroscopy for unambiguous metabolic profiling of complex mixtures

Unambiguous identification of individual metabolites present in complex mixtures such as biofluids constitutes a crucial prerequisite for quantitative metabolomics, toward better understanding of biochemical processes in living systems. Increasing the dimensionality of a given NMR correlation experiment is the natural solution for resolving spectral overlap. However, in the context of metabolites, natural abundance acquisition of ¹H and ¹³C NMR data virtually excludes the use of higher dimensional NMR experiments (3D, 4D, etc.) that would require unrealistically long acquisition times. Here, we introduce projection NMR techniques for studies of complex mixtures, and we show how discrete sets of projection spectra from higher dimensional NMR experiments are obtained in a reasonable time frame, in order to capture essential information necessary to resolve assignment ambiguities caused by signal overlap in conventional 2D NMR spectra. We determine optimal projection angles where given metabolite resonances will have the least overlap, to obtain distinct metabolite assignment in complex mixtures. The method is demonstrated for a model mixture composition made of ornithine, putrescine and arginine for which acquisition of a single 2D projection of a 3D ¹H–¹³C TOCSY‐HSQC spectrum allows to disentangle the metabolite signals and to access to complete profiling of this model mixture in the targeted 2D projection plane. Copyright © 2010 John Wiley & Sons, Ltd.     

NMR and pattern recognition methods in metabolomics: From data acquisition to biomarker discovery: A review

Metabolomics is the discipline where endogenous and exogenous metabolites are assessed, identified and quantified in different biological samples. Metabolites are crucial components of biological system and highly informative about its functional state, due to their closeness to functional endpoints and to the organism's phenotypes. Nuclear Magnetic Resonance (NMR) spectroscopy, next to Mass Spectrometry (MS), is one of the main metabolomics analytical platforms. The technological developments in the field of NMR spectroscopy have enabled the identification and quantitative measurement of the many metabolites in a single sample of biofluids in a non-targeted and non-destructive manner. Combination of NMR spectra of biofluids and pattern recognition methods has driven forward the application of metabolomics in the field of biomarker discovery. The importance of metabolomics in diagnostics, e.g. in identifying biomarkers or defining pathological status, has been growing exponentially as evidenced by the number of published papers. In this review, we describe the developments in data acquisition and multivariate analysis of NMR-based metabolomics data, with particular emphasis on the metabolomics of Cerebrospinal Fluid (CSF) and biomarker discovery in Multiple Sclerosis (MScl).     

Application of quantitative artificial neural network analysis to 2D NMR spectra of hydrocarbon mixtures

Understanding relationships between the structure and composition of molecular mixtures and their chemical properties is a main industrial aim. One central field of research is oil chemistry where the key question is how the molecular characteristics of composite hydrocarbon mixtures can be associated with the macroscopic properties of the oil products. Apparently these relationships are complex and often nonlinear and therefore call for advanced spectroscopic techniques. An informative and an increasingly used approach is two-dimensional nuclear magnetic resonance (2D NMR) spectroscopy. In the case of composite hydrocarbons the application of 2D NMR methodologies in a quantitative manner pose many technical difficulties, and, in any case, the resulting spectra contain many overlapping resonances that challenge the analytical work. Here, we present a general methodology, based on quantitative artificial neural network (ANN) analysis, to resolve overlapping information in 2D NMR spectra and to simultaneously assess the relative importance of multiple spectral variables on the sample properties. The results in a set of 2D NMR spectra of oil samples illustrate, first, that use of ANN analysis for quantitative purposes is feasible also in 2D and, second, that this methodology offers an intrinsic opportunity to assess the complex and nonlinear relationships between the molecular composition and sample properties. The presented ANN methodology is not limited to the analysis of NMR spectra but can also be applied in a manner similar to other (multidimensional) spectroscopic data.     

Targeted acquisition for real-time NMR spectroscopy

A target-oriented approach for the acquisition of information in biomolecular NMR spectroscopy is being developed. This approach combines concurrent data accumulation, processing, and monitoring of spectral quality. Real-time estimation of parameters allows acquisition to be stopped when results are complete and have a specified precision. The technique is based on multidimensional decomposition, which can process incomplete data. An incremental nonuniform sampling scheme ensures the optimization of resolution sensitivity. To validate this method, 3D HNCO spectra of three biomolecular systems (8 kDa ubiquitin, 22 kDa barstar-barnase complex, and 82 kDa malate synthase G) are processed incrementally at small acquisition time steps. The range of molecular sizes illustrates applicability in both sample- and sensitivity-limited regimes. In each case, the target was to acquire all backbone resonances in the spectra. For the three systems, the targets are achieved after 4.5 min, 1.6 h, and 22 h of acquisition time, respectively. A number of other targets that can be similarly monitored as a function of time are discussed.     

Metabolomics of meat exudate: Its potential to evaluate beef meat conservation and aging

In this study we analyzed the exudate of beef to evaluate its potential as non invasive sampling for nuclear magnetic resonance (NMR) based metabolomic analysis of meat samples. Exudate, as the natural juice from raw meat, is an easy to obtain matrix that it is usually collected in small amounts in commercial meat packages. Although meat exudate could provide complete and homogeneous metabolic information about the whole meat piece, this sample has been poorly studied. Exudates from 48 beef samples of different breeds, cattle and storage times have been studied by ¹H NMR spectroscopy. The liquid exudate spectra were compared with those obtained by High Resolution Magic Angle Spinning (HRMAS) of the original meat pieces. The close correlation found between both spectra (>95% of coincident peaks in both registers; Spearman correlation coefficient = 0.945) lead us to propose the exudate as an excellent alternative analytical matrix with a view to apply meat metabolomics. 60 metabolites could be identified through the analysis of mono and bidimensional exudate spectra, 23 of them for the first time in NMR meat studies. The application of chemometric tools to analyze exudate dataset has revealed significant metabolite variations associated with meat aging. Hence, NMR based metabolomics have made it possible both to classify meat samples according to their storage time through Principal Component Analysis (PCA), and to predict that storage time through Partial Least Squares (PLS) regression.     

"Multi-scan single shot" quantitative 2D NMR: a valuable alternative to fast conventional quantitative 2D NMR

Quantitative Ultrafast (UF) 2D NMR is a very promising methodology enabling the acquisition of 2D spectra in a single scan. The analytical performances of UF 2D NMR have been highly increased in the last few years, however little is known about the sensitivity of ultrafast experiments versus conventional 2D NMR. A fair and relevant comparison has to consider the Signal-to-Noise Ratio (SNR) per unit of time, in order to answer the following question: for a given experiment time, should we run a conventional 2D experiment or is it preferable to accumulate ultrafast acquisitions? To answer this question, we perform here a systematic comparison between accumulated ultrafast experiments and conventional ones, for different experiment durations. Sensitivity issues and other analytical aspects are discussed for the COSY experiment in the context of quantitative analysis. The comparison is first carried out on a model sample, and then extended to model metabolic mixtures. The results highlight the high analytical performance of the "multi-scan single shot" approach versus conventional 2D NMR acquisitions. This result is attributed to the absence of t(1) noise in spatially encoded experiments. The multi-scan single shot approach is particularly interesting for quantitative applications of 2D NMR, whose occurrence in the literature has been greatly increasing in the last few years.     

Very fast two-dimensional NMR spectroscopy for real-time investigation of dynamic events in proteins on the time scale of seconds

We demonstrate for different protein samples that 2D 1H-15N correlation NMR spectra can be recorded in a few seconds of acquisition time using a new band-selective optimized flip-angle short-transient heteronuclear multiple quantum coherence experiment. This has enabled us to measure fast hydrogen-deuterium exchange rate constants along the backbone of a small globular protein fragment by real-time 2D NMR.     

Solution-State 2D NMR Spectroscopy of Mixtures HyperpolarizedUsing Optically Polarized Crystals

The HYPNOESYS method (Hyperpolarized NOE System), which relies on the dissolution of optically polarized crystals, has recently emerged as a promising approach to enhance the sensitivity of NMR spectroscopy in the solution state. However, HYPNOESYS is a single-shot method that is not generally compatible with multidimensional NMR. Here we show that 2D NMR spectra can be obtained from HYPNOESYS-polarized samples, using single-scan acquisition methods. The approach is illustrated with a mixture of terpene molecules and a benchtop NMR spectrometer, paving the way to a sensitive, information-rich and affordable analytical method.     

Absolute Minimal Sampling of Homonuclear 2D NMR TOCSY Spectra for High-Throughput Applications of Complex Mixtures

Modern applications of 2D NMR spectroscopy to diagnostic screening, metabolomics, quality control, and other high-throughput applications are often limited by the time-consuming sampling requirements along the indirect time domain t₁. 2D total correlation spectroscopy (TOCSY) provides unique spin connectivity information for the analysis of a large number of compounds in complex mixtures, but standard methods typically require >100 t₁ increments for an accurate spectral reconstruction, rendering these experiments ineffective for high-throughput applications. For a complex metabolite mixture it is demonstrated that absolute minimal sampling (AMS), based on direct fitting of resonance frequencies and amplitudes in the time domain, yields an accurate spectral reconstruction of TOCSY spectra using as few as 16 t₁ points. This permits the rapid collection of homonuclear 2D NMR experiments at high resolution with measurement times that previously were only the realm of 1D experiments.     

UltraSOFAST HMQC NMR and the repetitive acquisition of 2D protein spectra at Hz rates

Following unidirectional biophysical events such as the folding of proteins or the equilibration of binding interactions, requires experimental methods that yield information at both atomic-level resolution and at high repetition rates. Toward this end a number of different approaches enabling the rapid acquisition of 2D NMR spectra have been recently introduced, including spatially encoded "ultrafast" 2D NMR spectroscopy and SOFAST HMQC NMR. Whereas the former accelerates acquisitions by reducing the number of scans that are necessary for completing arbitrary 2D NMR experiments, the latter operates by reducing the delay between consecutive scans while preserving sensitivity. Given the complementarities between these two approaches it seems natural to combine them into a single tool, enabling the acquisition of full 2D protein NMR spectra at high repetition rates. We demonstrate here this capability with the introduction of "ultraSOFAST" HMQC NMR, a spatially encoded and relaxation-optimized approach that can provide 2D protein correlation spectra at approximately 1 s repetition rates for samples in the approximately 2 mM concentration range. The principles, relative advantages, and current limitations of this new approach are discussed, and its application is exemplified with a study of the fast hydrogen-deuterium exchange characterizing amide sites in Ubiquitin.     

Absolute Minimal Sampling of Homonuclear 2D NMR TOCSY Spectra for High‐Throughput Applications of Complex Mixtures

Modern applications of 2D NMR spectroscopy to diagnostic screening, metabolomics, quality control, and other high‐throughput applications are often limited by the time‐consuming sampling requirements along the indirect time domain t ₁. 2D total correlation spectroscopy (TOCSY) provides unique spin connectivity information for the analysis of a large number of compounds in complex mixtures, but standard methods typically require >100 t ₁ increments for an accurate spectral reconstruction, rendering these experiments ineffective for high‐throughput applications. For a complex metabolite mixture it is demonstrated that absolute minimal sampling (AMS), based on direct fitting of resonance frequencies and amplitudes in the time domain, yields an accurate spectral reconstruction of TOCSY spectra using as few as 16 t ₁ points. This permits the rapid collection of homonuclear 2D NMR experiments at high resolution with measurement times that previously were only the realm of 1D experiments.     

Real-time monitoring of chemical transformations by ultrafast 2D NMR spectroscopy

An approach enabling the acquisition of 2D nuclear magnetic resonance (NMR) spectra within a single scan has been recently proposed. A promising application opened up by this "ultrafast" data acquisition format concerns the monitoring of chemical transformations as they happen, in real time. The present paper illustrates some of this potential with two examples: (i) following an H/D exchange process that occurs upon dissolving a protonated protein in D2O, and (ii) real-time in situ tracking of a transient Meisenheimer complex that forms upon rapidly mixing two organic reactants inside the NMR observation tube. The first of these measurements involved acquiring a train of 2D 1H-15N HSQC NMR spectra separated by ca. 4 s; following an initial dead time, this allowed us to monitor the kinetics of hydrogen exchange in ubiquitin at a site-resolved level. The second approach enabled us to observe, within ca. 2 s after the triggering of the reaction, a competition between thermodynamic and kinetic controls via changes in a series of 2D TOCSY patterns. The real-time dynamic experiments hereby introduced thus add to an increasing family of fast characterization techniques based on 2D NMR; their potential and limitations are briefly discussed.     

Assessing 2D electrophoretic mobility spectroscopy (2D MOSY) for analytical applications

Electrophoretic displacement of charged entity phase modulates the spectrum acquired in electrophoretic NMR experiments, and this modulation can be presented via 2D FT as 2D mobility spectroscopy (MOSY) spectra. We compare in various mixed solutions the chemical selectivity provided by 2D MOSY spectra with that provided by 2D diffusion‐ordered spectroscopy (DOSY) spectra and demonstrate, under the conditions explored, a superior performance of the former method. 2D MOSY compares also favourably with closely related LC‐NMR methods. The shape of 2D MOSY spectra in complex mixtures is strongly modulated by the pH of the sample, a feature that has potential for areas such as in drug discovery and metabolomics. Copyright © 2016 The Authors. Magnetic Resonance in Chemistry published by John Wiley & Sons Ltd.     

Sub-second 2D NMR spectroscopy at sub-millimolar concentrations

A recently proposed protocol enables the acquisition of two-dimensional nuclear magnetic resonance (2D NMR) spectra within a single scan. A promising application opened up by this new data acquisition mode concerns its combination with active nuclear polarization methods, whereby spectroscopy is carried out on analytes whose spin magnetizations have been significantly enhanced over their Boltzmann thermal values. The present paper explores the potential of such combination, with the acquisition of peptide and protein 2D NMR 1H correlation spectra recorded after the samples had been subject to laser-driven chemically induced dynamic nuclear polarization (CIDNP). It is demonstrated that the speed and sensitivity enhancement afforded by these combined processes enables the acquisition of quality 2D NMR data sets within a fraction of a second, at analyte concentrations that are under 1 mM.     

Single-scan NMR spectroscopy at arbitrary dimensions

Multidimensional nuclear magnetic resonance (NMR) provides one of the foremost analytical tools available to elucidate the structure and dynamics of complex molecules in their native states. Executing this kind of experiment generally requires collecting an n-dimensional time-domain signal S, from which the spectrum arises via an appropriate Fourier analysis of its various time variables. This time-domain signal is actually measured directly only along one of the time axes, while the effects introduced by the remaining time variables are monitored via a parametric incrementation of their values throughout independent experiments. Two-dimensional (2D) NMR experiments thus usually require longer acquisition times than unidimensional experiments, 3D NMR is orders-of-magnitude more time consuming than 2D spectroscopy, etc. Very recently, we proposed and demonstrated an approach whereby data acquisition in 2D NMR can be parallelized, enabling the collection of complete 2D spectral sets within a single transient. The present paper discusses the extension of this 2D NMR methodology to an arbitrary number of dimensions. The principles of the ensuing ultrafast n-dimensional NMR approach are described, and a variety of homo- and heteronuclear 3D and 4D NMR spectra collected within a fraction of a second are presented.     

Identification of metabolites in coriander seeds (Coriandrum Sativum L.) aided by ultrahigh resolution total correlation NMR spectroscopy

NMR is a fast method for obtaining a holistic snapshot of the metabolome and also offers quantitative information without separating the compounds present in a complex mixture. Identification of the metabolites present in a plant extract sample is a crucial step for all plant metabolomics studies. In the present work, we used various two dimensional (2D) NMR methods such as J-resolved NMR, total correlation spectroscopy (TOCSY), and heteronuclear single quantum coherence sensitivity enhanced NMR spectroscopy for the identification of 36 common metabolites present in Coriandrum sativum L. seed extract. The identified metabolites belong to the following classes: organic acids, amino acids, and carbohydrates. ¹H NMR spectra of such complex mixtures in general display tremendous signal overlap due to the presence of a large number of metabolites with closely resonating multiplet signals. This signal overlapping leads to ambiguity in an assignment, and hence, identification of metabolites becomes tedious or impossible in many cases. Therefore, the utility of pure-shift proton spectrum along the indirect (F₁) dimension of the F₁-PSYCHE-TOCSY spectrum is demonstrated for overcoming ambiguity in assignment of metabolites in crowded spectral regions from Coriandrum sativum L. seed extract sample. Because pure-shift NMR methods yield ultrahigh resolution spectrum (i.e., a singlet peak per chemical site) along one or more dimensions, such spectra provide better identification of metabolites compared with regular 2D TOCSY where signal overlap and peak distortions lead to ambiguity in the assignment. Nine metabolites were unambiguously assigned by pure-shift F₁-PSYCHE-TOCSY spectrum, which was unresolved in regular TOCSY spectrum.     

Fast and high-resolution stereochemical analysis by nonuniform sampling and covariance processing of anisotropic natural abundance 2D 2H NMR datasets

Natural abundance deuterium (NAD) 2D NMR spectroscopy using chiral or achiral liquid crystals is an efficient analytical tool for the stereochemical analysis of enantio- or diastereomers by the virtue of proton-to-deuterium substitution. In particular, it allows the measurement of enantiopurity of organic synthetic molecules or the determination of the natural isotopic (1)H/(2)H fractionation in biological molecules, such as fatty acid methyl esters (FAME). So far, the NAD 2D spectra of solutes were acquired by using uniform sampling (US) and processed by conventional 2D Fourier transform (FT), which could result in long measurement times for medium-sized analytes or low solute concentrations. Herein, we demonstrate that this conventional approach can be advantageously replaced by nonuniform sampling (NUS) processed by covariance (Cov) transform. This original spectral reconstruction provides a significant enhancement of spectral resolution, as well as a reduction of measurement times. The application of Cov to NUS data has required the introduction of a regularization procedure in the time domain for the indirect dimension. The analytical potential of combining Cov and NUS is demonstrated by measuring the enantiomeric excess of a scalemic mixture of 2-ethyloxirane and by determining the diastereomeric excess of methyl vernoleate, a natural FAME. These two organic compounds were aligned in a polypeptide (poly(γ-benzyl-L-glutamate)) mesophase. In the case of NAD 2D NMR spectroscopy, we show that Cov and NUS methods allow a decrease in measurement time by a factor of two compared with Cov applied to US data and a factor of four compared with FT applied to US data.     

Real-time 2D NMR identification of analytes undergoing continuous chromatographic separation

We have recently proposed and demonstrated an approach that enables the acquisition of multidimensional nuclear magnetic resonance (NMR) spectra within a single scan. A promising application opened up by this new accelerated form of data acquisition concerns the possibility of monitoring in real time the chemical nature of analytes subject to a continuous flow. The present paper illustrates such potential, with the real-time acquisition of a series of 2D 1H NMR spectra arising from a mixture of compounds subject to a continuous liquid chromatography (LC) separation. This real-time 2D NMR identification of chemicals eluted minutes apart under usual LC-NMR conditions differs from the way in which LC-2D NMR has hitherto been carried out, which relies on stopped-flow modes of operations whereby fractions are first collected and then subject to individual, aliquot-by-aliquot analyses. The real-time LC-2D NMR experiment hereby introduced can be implemented in a straightforward manner using modern commercial LC-NMR hardware, thus opening up immediate possibilities in high-throughput characterizations of complex molecules.