Revisiting aliasing noise to build more robust sparsity in nonuniform sampling 2D-NMR

A continuing priority is to better understand and resolve the barriers to using nonuniform sampling (NUS) in challenging small molecule 2D NMR with subsampling of the Nyquist grid (a.k.a. coverage) below 50%. Possible causes for artifacts, often termed sampling noise, in 1D-NUS of 2D-NMR are revisited here, where weak aliasing artifacts are a growing concern as NUS becomes sparser. As NUS schedules become sparser, repeat sequences are shown to occur in the dense sampling regions early in the sampling schedule, causing aliasing artifacts in resulting spectra. An intuitive screening approach that detects patterns in sampling schedules based on a convolutional filter was implemented. Sampling schedules that have low proportions of repeat sequences show significantly reduced artifacts. Another route to remediate early repeat sequences is a short period of uniform sampling at the beginning of the schedule, which also leads to a significant suppression of unwanted sampling noise. Combining the repeat sequence filter with a survey of HSQC and LR-HSQMBC experiments, it is shown that very short initial uniform regions of about 2%-4% of the sampling space can ameliorate repeat sequences in sparser NUS and lead to robust spectral reconstructions by iterative soft thresholding (IST), even when the point spread function is unchanged. Using the principles developed here, a suite of 'one-click' schedules was developed for broader use.

High-field ex vivo and in vivo two-dimensional nuclear magnetic resonance spectroscopy in murine brain: Resolving and exploring the molecular environment

The structural and chemical complexities within the brain pose a challenge that few noninvasive techniques can tackle with the dexterity of nuclear magnetic resonance (NMR) spectroscopy. Still, even with the advent of ultrahigh fields and of cryogenically cooled coils for in vivo research, the superposition of metabolic resonances arising from the brain remains a challenge. The present study explores the potential to tackle this milieu using a combination of two-dimensional (2D) NMR techniques, implemented on murine brains in vivo at 15.2 T and ex vivo at 14.1 T. While both experiments were affected by substantial inhomogeneous broadenings conveying distinct elongated lineshapes to the cross-peaks, the ability of increased fields to resolve off-diagonal resonances was clear. A comparison between the corresponding conventional and double quantum-filtered correlated spectroscopy traces enabled an improved assignment of in vivo resonances on the basis of more sensitive ex vivo 2D acquisitions, foremost on the basis of homonuclear cross-relaxation-driven correlations for peaks resonating downfield from water, and of heteronuclear correlations at natural abundance for the upfield protons. With the aid of such 2D correlations approximately 29 metabolites could be resolved and identified. This enhanced resolution was used to explore features related to the metabolites' diffusivities, their exposure to water, and their facility to undergo magnetization transfers to amide/amine/hydroxyl resonances. Cross-peaks from main murine brain biomolecules, including choline, creatine, γ-aminobutyric acid, N-acetyl aspartate, glutamine, and glutamate, showed enhancements in several of these various features, opening interesting vistas about metabolite compartmentalization as viewed by these 2D NMR experiments.

Drug-Polymer Interactions in Acetaminophen/Hydroxypropylmethylcellulose Acetyl Succinate Amorphous Solid Dispersions Revealed by Multidimensional Multinuclear Solid-State NMR Spectroscopy

The bioavailability of insoluble crystalline active pharmaceutical ingredients (APIs) can be enhanced by formulation as amorphous solid dispersions (ASDs). One of the key factors of ASD stabilization is the formation of drug-polymer interactions at the molecular level. Here, we used a range of multidimensional and multinuclear nuclear magnetic resonance (NMR) experiments to identify these interactions in amorphous acetaminophen (paracetamol)/hydroxypropylmethylcellulose acetyl succinate (HPMC-AS) ASDs at various drug loadings. At low drug loading (<20 wt %), we showed that 1H-13C through-space heteronuclear correlation experiments identify proximity between aromatic protons in acetaminophen with cellulose backbone protons in HPMC-AS. We also show that 14N-1H heteronuclear multiple quantum coherence (HMQC) experiments are a powerful approach in probing spatial interactions in amorphous materials and establish the presence of hydrogen bonds (H-bond) between the amide nitrogen of acetaminophen with the cellulose ring methyl protons in these ASDs. In contrast, at higher drug loading (40 wt %), no acetaminophen/HPMC-AS spatial proximity was identified and domains of recrystallization of amorphous acetaminophen into its crystalline form I, the most thermodynamically stable polymorph, and form II are identified. These results provide atomic scale understanding of the interactions in the acetaminophen/HPMC-AS ASD occurring via H-bond interactions.

Quantitative NMR-Based Biomedical Metabolomics: Current Status and Applications

Nuclear Magnetic Resonance (NMR) spectroscopy is a quantitative analytical tool commonly utilized for metabolomics analysis. Quantitative NMR (qNMR) is a field of NMR spectroscopy dedicated to the measurement of analytes through signal intensity and its linear relationship with analyte concentration. Metabolomics-based NMR exploits this quantitative relationship to identify and measure biomarkers within complex biological samples such as serum, plasma, and urine. In this review of quantitative NMR-based metabolomics, the advancements and limitations of current techniques for metabolite quantification will be evaluated as well as the applications of qNMR in biomedical metabolomics. While qNMR is limited by sensitivity and dynamic range, the simple method development, minimal sample derivatization, and the simultaneous qualitative and quantitative information provide a unique landscape for biomedical metabolomics, which is not available to other techniques. Furthermore, the non-destructive nature of NMR-based metabolomics allows for multidimensional analysis of biomarkers that facilitates unambiguous assignment and quantification of metabolites in complex biofluids.

Alternating Copolymer of Double Four Ring Silicate and Dimethyl Silicone Monomer-PSS-1

A new copolymer consisting of double four ring (D4R) silicate units linked by dimethylsilicone monomer referred to as polyoligosiloxysilicone number one (PSS-1) was synthesized. The D4R building unit is provided by hexamethyleneimine cyclosilicate hydrate crystals, which were dehydrated and reacted with dichlorodimethylsilane. The local structure of D4R silicate units and dimethyl silicone monomers was revealed by multidimensional solid-state NMR, FTIR and modeling. On average, D4R silicate units have 6.8 silicone linkages. Evidence for preferential unidirectional growth and chain ordering within the PSS-1 copolymer was provided by STEM and TEM. The structure of PSS-1 copolymer consists of twisted columns of D4R silicate units with or without cross-linking. Both models are consistent with the spectroscopic, microscopic and physical properties. PSS-1 chains are predicted to be mechanically strong compared to silicones such as PDMS, yet more flexible than rigid silica materials such as zeolites.

Fast acquisition of multidimensional NMR spectra of solids and mesophases using alternative sampling methods

Unique information about the atom-level structure and dynamics of solids and mesophases can be obtained by the use of multidimensional nuclear magnetic resonance (NMR) experiments. Nevertheless, the acquisition of these experiments often requires long acquisition times. We review here alternative sampling methods, which have been proposed to circumvent this issue in the case of solids and mesophases. Compared to the spectra of solutions, those of solids and mesophases present some specificities because they usually display lower signal-to-noise ratios, non-Lorentzian line shapes, lower spectral resolutions and wider spectral widths. We highlight herein the advantages and limitations of these alternative sampling methods. A first route to accelerate the acquisition time of multidimensional NMR spectra consists in the use of sparse sampling schemes, such as truncated, radial or random sampling ones. These sparsely sampled datasets are generally processed by reconstruction methods differing from the Discrete Fourier Transform (DFT). A host of non-DFT methods have been applied for solids and mesophases, including the G-matrix Fourier transform, the linear least-square procedures, the covariance transform, the maximum entropy and the compressed sensing. A second class of alternative sampling consists in departing from the Jeener paradigm for multidimensional NMR experiments. These non-Jeener methods include Hadamard spectroscopy as well as spatial or orientational encoding of the evolution frequencies. The increasing number of high field NMR magnets and the development of techniques to enhance NMR sensitivity will contribute to widen the use of these alternative sampling methods for the study of solids and mesophases in the coming years.

Non-uniform sampling: post-Fourier era of NMR data collection and processing

The invention of multidimensional techniques in the 1970s revolutionized NMR, making it the general tool of structural analysis of molecules and materials. In the most straightforward approach, the signal sampling in the indirect dimensions of a multidimensional experiment is performed in the same manner as in the direct dimension, i.e. with a grid of equally spaced points. This results in lengthy experiments with a resolution often far from optimum. To circumvent this problem, numerous sparse-sampling techniques have been developed in the last three decades, including two traditionally distinct approaches: the radial sampling and non-uniform sampling. This mini review discusses the sparse signal sampling and reconstruction techniques from the point of view of an underdetermined linear algebra problem that arises when a full, equally spaced set of sampled points is replaced with sparse sampling. Additional assumptions that are introduced to solve the problem, as well as the shape of the undersampled Fourier transform operator (visualized as so-called point spread function), are shown to be the main differences between various sparse-sampling methods.

hNCOcanH pulse sequence and a robust protocol for rapid and unambiguous assignment of backbone ((1)H(N), (15)N and (13)C') resonances in (15)N/(13)C-labeled proteins

A three-dimensional nuclear magnetic resonance (NMR) pulse sequence named as hNCOcanH has been described to aid rapid sequential assignment of backbone resonances in (15)N/(13)C-labeled proteins. The experiment has been derived by a simple modification of the previously described HN(C)N pulse sequence [Panchal et al., J. Biomol. NMR 20 (2001) 135-147]; t2 evolution is used to frequency label (13)C' rather than (15)N (similar trick has also been used in the design of hNCAnH pulse sequence from hNcaNH [Frueh et al., JACS, 131 (2009) 12880-12881]). The modification results in a spectrum equivalent to HNCO, but in addition to inter-residue correlation peaks (i.e. Hi , Ci-1), the spectrum also contains additional intra-residue correlation peaks (i.e. Hi-1 , Ci-1) in the direct proton dimension which has maximum resolution. This is the main strength of the experiment and thus, even a small difference in amide (1) H chemical shifts (5-6 Hz) can be used for establishing a sequential connectivity. This experiment in combination with the HNN experiment described previously [Panchal et al., J. Biomol. NMR 20 (2001) 135-147] leads to a more robust assignment protocol for backbone resonances ((1) H(N) , (15)N) than could be derived from the combination of HNN and HN(C)N experiments [Bhavesh et al., Biochemistry, 40 (2001) 14727-14735]. Further, this new protocol enables assignment of (13)C' resonances as well. We believe that the experiment and the protocol presented here will be of immense value for structural-and functional-proteomics research by NMR. Performance of this experiment has been demonstrated using (13)C/(15)N labeled ubiquitin.

A double-Fourier approach to enhance the efficiency of the indirect domain sampling in 2D NMR

The relatively long times that may be involved in high-resolution two-dimensional nuclear magnetic resonance (2D NMR) have stimulated the search for alternative schemes to collect these data. Particularly onerous situations arise when both high-resolution and large spectral widths are sought along the indirect domain. Strategies proposed for dealing with such cases include folding-over procedures, Hadamard encoding, and nonlinear data sampling. This communication discusses an alternative strategy, which exploits a partial prior knowledge regarding the position of the NMR resonances along the indirect domain together with customized excitations for every particular t1 increment, to achieve an optimal sampling in terms of resolution and bandwidth. On the basis of such optimized encoding of the indirect-domain evolution, which can easily be coped with by modern spectrometers, it becomes possible to maximize the resolution of fine structures without compromising on the spectral bandwidths. The processing of the resulting data along the indirect domain is based on the use of two serially applied discrete Fourier transforms; one to distinguish the main bands in the spectrum and the other to resolve the latter's fine features. A number of simple heteronuclear correlation experiments illustrating the significant acquisition time savings and simultaneous improvements in resolution that can be achieved with the resulting double-Fourier encoding procedure are illustrated.